phd medical data science

Master of Science in Health Data Science

Leverage your skills in statistics, computer science & software engineering and begin your career in the booming field of health data science

The Master of Science (SM) in Health Data Science is designed to provide rigorous quantitative training and essential statistical and computing skills needed to manage and analyze health science data to address important questions in public health and biomedical sciences.

The 16-month program blends strong statistical and computational training to solve emerging problems in public health and the biomedical sciences. This training will enable students to manage and analyze massive, noisy data sets and learn how to interpret their findings. The program will provide training in three principal pillars of health data science: statistics, computing, and health sciences.

Students in the program will learn to:

• Wrangle and transform data to perform meaningful analyses
• Visualize and interpret data and effectively communicate results and findings
• Apply statistical methods to draw scientific conclusions from data
• Utilize statistical models and machine learning
• Apply methods for big data to reveal patterns, trends, and associations
• Employ high-performance scientific computing and software engineering
• Collaborate with a team on a semester-long, data driven research project

The SM in Health Data Science is designed to be a terminal professional degree, giving students essential skills for the job market. At the same time, it provides a strong foundation for students interested in obtaining a PhD in biostatistics or other quantitative or computational science with an emphasis in data science and its applications in health science.

News from the School

From public servant to public health student

Exploring the intersection of health, mindfulness, and climate change

Conference aims to help experts foster health equity

Building solidarity to face global injustice

• Skip to Content
• Catalog Home
• Biomedical Data Science, Ph.D.

The current explosion of biomedical data provides an awesome opportunity to improve understanding of the mechanisms of disease and ultimately to improve human health care. However, fully harnessing the power of high-dimensional, heterogeneous data requires a new blend of skills including programming, data management, data analysis, and machine learning.

Blending the best of statistics and computer sciences, biostatistics and biomedical informatics, this program provides students the training they need to make sense of large-scale biomedical data, and to be scientific leaders in the team science that invariably accompanies such data. Unique features of the program include cross-training in computer science and biostatistics, and research rotations mentored by a program faculty member jointly with a scientific collaborator.

Please consult the table below for key information about this degree program’s admissions requirements. The program may have more detailed admissions requirements, which can be found below the table or on the program’s website.

Graduate admissions is a two-step process between academic programs and the Graduate School. Applicants must meet the minimum requirements of the Graduate School as well as the program(s). Once you have researched the graduate program(s) you are interested in, apply online .

Potential students include both those with bachelor’s degrees in an area of data-science (e.g., computer science, statistics), as well as health professionals and clinicians (e.g., M.D.'s, Pharm.D.'s, R.N.'s). It is expected that admitted candidates will have demonstrated an aptitude for computer science and math, fundamental programming skills, knowledge of data structures and algorithms, and at least two semesters of college calculus. We will however consider candidates who have a wide range of undergraduate backgrounds; providing opportunities to develop necessary skills immediately upon entering the program.

Applying to the Program:

• A formal online application with required fee through the UW–Madison Graduate School
• Three letters of recommendation
• Transcripts from each higher-education institution attended
• A statement of purpose
• Applicants whose native language is not English, or whose undergraduate instruction was not in English, must provide an English proficiency test score (TOEFL, MELAB, or IELTS)
• Evidence of quantitative preparation, including at least two semesters of college calculus (similar to MATH 221 – MATH 222 ) and either a course in linear algebra (similar to MATH 340 ) or courses in programming and data structures

For additional information about admission to the program, see  PhD Program in Biomedical Data Science  on the department website.

Graduate School Resources

Resources to help you afford graduate study might include assistantships, fellowships, traineeships, and financial aid.  Further funding information is available from the Graduate School. Be sure to check with your program for individual policies and restrictions related to funding.

PROGRAM RESOURCES

The program is designed such that almost all students who are accepted to the program will receive guaranteed funding for five years. This funding may take a number of forms including, but not limited to training grants, teaching assistantships, and research assistantships. For more information about funding opportunities, see Graduate Assistantships .

Minimum Graduate School Requirements

Major requirements.

Review the Graduate School minimum academic progress and degree requirements , in addition to the program requirements listed below.

MODE OF INSTRUCTION

Mode of instruction definitions.

Accelerated: Accelerated programs are offered at a fast pace that condenses the time to completion. Students typically take enough credits aimed at completing the program in a year or two.

Evening/Weekend: ​Courses meet on the UW–Madison campus only in evenings and/or on weekends to accommodate typical business schedules.  Students have the advantages of face-to-face courses with the flexibility to keep work and other life commitments.

Face-to-Face: Courses typically meet during weekdays on the UW-Madison Campus.

Hybrid: These programs combine face-to-face and online learning formats.  Contact the program for more specific information.

Online: These programs are offered 100% online.  Some programs may require an on-campus orientation or residency experience, but the courses will be facilitated in an online format.

CURRICULAR REQUIREMENTS

Required courses, graduate school policies.

The  Graduate School’s Academic Policies and Procedures  provide essential information regarding general university policies. Program authority to set degree policies beyond the minimum required by the Graduate School lies with the degree program faculty. Policies set by the academic degree program can be found below.

Major-Specific Policies

Prior coursework, graduate work from other institutions.

With program approval, students are allowed to count no more than 9 credits of graduate course work from other institutions toward the graduate degree credit and graduate course work (50%) requirements. Course work earned ten years or more prior to admission to a doctoral degree is not allowed to satisfy requirements.

UW–Madison Undergraduate

This program follows the Graduate School's policy for Satisfying Requirements with Coursework from Undergraduate Career at UW–Madison.

UW–Madison University Special

This program follows  the Graduate School's policy for Transfer from UW–Madison University Special Student Career at UW–Madison . 

This program follows the Graduate School's Probation policy.

ADVISOR / COMMITTEE

All students are required to conduct a yearly progress report meeting with their advisor, scheduled by December 17 and completed by April 30.

CREDITS PER TERM ALLOWED

Time limits.

This program follows the Graduate School's Time Limits policy.

grievances and appeals

These resources may be helpful in addressing your concerns:

• Bias or Hate Reporting  
• Graduate Assistantship Policies and Procedures
• Office of the Provost for Faculty and Staff Affairs
• Dean of Students Office (for all students to seek grievance assistance and support)
• Employee Assistance (for personal counseling and workplace consultation around communication and conflict involving graduate assistants and other employees, post-doctoral students, faculty and staff)
• Employee Disability Resource Office (for qualified employees or applicants with disabilities to have equal employment opportunities)
• Graduate School (for informal advice at any level of review and for official appeals of program/departmental or school/college grievance decisions)
• Office of Compliance (for class harassment and discrimination, including sexual harassment and sexual violence)
• Office of Student Conduct and Community Standards (for conflicts involving students)
• Ombuds Office for Faculty and Staff (for employed graduate students and post-docs, as well as faculty and staff)
• Title IX (for concerns about discrimination)

Grievance Policy for Graduate Programs in the School of Medicine and Public Health

Any student in a School of Medicine and Public Health graduate program who feels that they have been treated unfairly in regards to educational decisions and/or outcomes or issues specific to the graduate program, including academic standing, progress to degree, professional activities, appropriate advising, and a program’s community standards by a faculty member, staff member, postdoc, or student has the right to complain about the treatment and to receive a prompt hearing of the grievance following these grievance procedures. Any student who discusses, inquiries about, or participates in the grievance procedure may do so openly and shall not be subject to intimidation, discipline, or retaliation because of such activity. Each program’s grievance advisor is listed on the “Research” tab of the SMPH intranet .

This policy does not apply to employment-related issues for Graduate Assistants in TA, PA and/or RA appointments.  Graduate Assistants will utilize the Graduate Assistantship Policies and Procedures (GAPP) grievance process to resolve employment-related issues.

This policy does not apply to instances when a graduate student wishes to report research misconduct.  For such reports refer to the UW-Madison Policy for Reporting Research Misconduct for Graduate Students and Postdoctoral Research Associates .

Requirements for Programs

The School of Medicine and Public Health Office of Basic Research, Biotechnology and Graduate Studies requires that each graduate program designate a grievance advisor, who should be a tenured faculty member, and will request the name of the grievance advisor annually.  The program director will serve as the alternate grievance advisor in the event that the grievance advisor is named in the grievance.  The program must notify students of the grievance advisor, including posting the grievance advisor’s name on the program’s Guide page and handbook.

The grievance advisor or program director may be approached for possible grievances of all types.  They will spearhead the grievance response process described below for issues specific to the graduate program, including but not limited to academic standing, progress to degree, professional activities, appropriate advising, and a program’s community standards.  They will ensure students are advised on reporting procedures for other types of possible grievances and are supported throughout the reporting process.  Resources on identifying and reporting other issues have been compiled by the Graduate School.

• The student is advised to initiate a written record containing dates, times, persons, and description of activities, and to update this record while completing the procedures described below.
• If the student is comfortable doing so, efforts should be made to resolve complaints informally between individuals before pursuing a formal grievance.
• Should a satisfactory resolution not be achieved, the student should contact the program’s grievance advisor or program director to discuss the complaint. The student may approach the grievance advisor or program director alone or with a UW-Madison faculty or staff member. The grievance advisor or program director should keep a record of contacts with regards to possible grievances.  The first attempt is to help the student informally address the complaint prior to pursuing a formal grievance. The student is also encouraged to talk with their faculty advisor regarding concerns or difficulties.
• If the issue is not resolved to the student’s satisfaction, the student may submit a formal grievance to the grievance advisor or program director in writing, within 60 calendar days from the date the grievant first became aware of, or should have become aware of with the exercise of reasonable diligence, the cause of the grievance.  To the fullest extent possible, a grievance shall contain a clear and concise statement of the grievance and indicate the issue(s) involved, the relief sought, the date(s) the incident or violation took place, and any specific policy involved.
• The grievance advisor or program director will convene a faculty committee composed of at least three members to manage the grievance.  Any faculty member involved in the grievance or who feels that they cannot be impartial may not participate in the committee.  Committee composition should reflect diverse viewpoints within the program.
• The faculty committee, through the grievance advisor or program director, will obtain a written response from the person or persons toward whom the grievance is directed. The grievance advisor or program director will inform this person that their response will be shared with the student filing the grievance.
• The grievance advisor or program director will share the response with the student filing the grievance.
• The faculty committee will make a decision regarding the grievance. The committee’s review shall be fair, impartial, and timely.  The grievance advisor or program director will report on the action taken by the committee in writing to both the student and the person toward whom the grievance was directed.
• The grievant will be notified in writing, within 5 business days of the written appeal, acknowledging receipt of the formal appeal and establishing a timeline for the review to be completed.
• The senior associate dean or their designee may request additional materials and/or arrange meetings with the grievant and/or others.  If meetings occur, the senior associate dean or their designee will meet with both the grievant and the person or persons toward whom the grievance is directed.
• The senior associate dean or their designee will assemble an ad hoc committee of faculty from outside of the student’s graduate program and ask them to prepare a written recommendation on whether to uphold or reverse the decision of the program on the student’s initial grievance.  The committee may request additional materials and/or arrange meetings with the grievant and/or others.  If meetings occur, the committee will meet with both the grievant and the person or persons toward whom the grievance is directed.
• The senior associate dean or their designee will make a final decision within 20 business days of receipt of the committee’s recommendation.
• The SMPH Office of Basic Research, Biotechnology, and Graduate Studies must store documentation of the grievance for seven years. Grievances that set a precedent may be stored indefinitely.
• The student may file an appeal of the School of Medicine and Public Health decision with the Graduate School.  See the Grievances and Appeals section of the Graduate School’s Academic Policies and Procedures .

Time Limits

Steps in the grievance procedures must be initiated and completed within the designated time periods except when modified by mutual consent. If the student fails to initiate the next step in the grievance procedure within the designated time period, the grievance will be considered resolved by the decision at the last completed step.

Take advantage of the Graduate School's  professional development resources to build skills, thrive academically, and launch your career. 

• Articulate the biological context of a research question and the scientific relevance of analysis results.
• Communicate with scientific and quantitative (computational and statistical) colleagues about data analysis goals, methods, and results.
• Extract the statistical or computational problems from a scientific problem. Develop, characterize, and implement suitable analysis methods to answer questions from biomedical data. Evaluate the validity of analysis methods.
• Analyze data; extract knowledge and guide decisions based on biomedical data. Organize data and software so that quantitative analyses are meaningful and reproducible.
• Critically evaluate quantitative approaches in the scientific literature.
• Evaluate and develop study designs and recognize limitations and potential biases in research data sets.
• Identify the ethical and regulatory issues surrounding a research project.
• As part of a biological, biomedical or population health investigative team, serve as the leader in the area of rigorous computational and statistical investigation.

Faculty:  Broman, Buchanan, Burnside, Chappell, Chen, Chung, Craven, Dewey, Doan, Dyer, Elwert, Gangnon, Gianola, Gitter, Keles, Kendziorski, Kim, Lu, Mao, Mumford, Newton (chair), Ong,  Palta, Patel, Peissig, Rosa, Rosenberg, Roy, Singh, Sorkness, Tang, Yandell, Velten, Wang, Yu, Zhang, Zhu

• Requirements
• Professional Development
• Learning Outcomes

Contact Information

Biostatistics and Medical Informatics School of Medicine and Public Health Biomedical Data Science, PhD [email protected] https://www.biostat.wisc.edu/

Shelley Maxted, Graduate Coordinator [email protected] 608-263-4826 4745 Medical Sciences Center 1300 University Ave Madison, WI 53706

Beth Bierman, Graduate Coordinator [email protected] 608-265-8649 4775b Medical Sciences Center 1300 University Ave Madison, WI 53706

Sushmita Roy, Director of PhD Program [email protected] 608-316-4453 3168 Discovery Building (WID) 333 N Randall Ave, Madison, WI 53715

Michael Newton, Biostatistics & Medical Informatics Chair [email protected] 608-262-0086 1245a, K6/434 Medical Sciences Center 1300 University Ave, Madison, WI 53706

Grievance Advisor, Colin Dewey, Professor [email protected] 608-263-7610 2128 Genetics-Biotechnology Center Building 425 Henry Mall, Madison, WI 53706

Graduate Program Handbook View Here

Graduate School grad.wisc.edu

• /​pdf/​
• Explore Graduate Opportunities
• Explore UW-​Madison's Undergraduate Opportunities
• Accounting and Information Systems
• African American Studies
• African Cultural Studies
• Agricultural and Applied Economics
• Agricultural and Life Sciences -​ College-​Wide
• Animal and Dairy Sciences
• Anthropology
• Art History
• Asian Languages and Cultures
• Atmospheric and Oceanic Sciences
• Bacteriology
• Biochemistry
• Biological Systems Engineering
• Biomedical Engineering
• Biomedical Data Science, M.S.
• Business -​ School-​Wide
• Cell and Regenerative Biology
• Chemical and Biological Engineering
• Chicana/​o and Latina/​o Studies
• Civil and Environmental Engineering
• Civil Society &​ Community Studies
• Classical and Ancient Near Eastern Studies
• Communication Arts
• Communication Sciences and Disorders
• Community and Environmental Sociology
• Computer Sciences
• Counseling Psychology
• Curriculum and Instruction
• Educational Leadership and Policy Analysis
• Educational Policy Studies
• Educational Psychology
• Electrical and Computer Engineering
• Engineering -​ College-​Wide
• Food Science
• Forest and Wildlife Ecology
• French and Italian
• Gaylord Nelson Institute for Environmental Studies
• Gender and Women's Studies
• German, Nordic, and Slavic
• Graduate -​ School-​Wide
• Horticulture
• Human Ecology -​ School-​Wide
• Industrial and Systems Engineering
• Information School
• Institute for Clinical and Translational Research
• Institute for Regional and International Studies
• Integrative Biology
• Journalism and Mass Communication
• Kinesiology
• La Follette School of Public Affairs
• Language Institute
• Language Sciences
• Law -​ School-​Wide
• Life Sciences Communication
• Management and Human Resources
• Materials Science and Engineering
• Mathematics
• Mead Witter School of Music
• Mechanical Engineering
• Medical Physics
• Medicine and Public Health -​ School-​Wide
• Nuclear Engineering and Engineering Physics
• Nursing -​ School-​Wide
• Nutritional Sciences
• Operations and Information Management
• Pharmacy -​ School-​Wide
• Planning and Landscape Architecture
• Plant Pathology
• Political Science
• Population Health Sciences
• Real Estate and Urban Land Economics
• Rehabilitation Psychology and Special Education
• Religious Studies
• Risk and Insurance
• Sandra Rosenbaum School of Social Work
• Soil Science
• Spanish and Portuguese
• Veterinary Medicine -​ School-​Wide
• Nondegree/​Visiting Student Guide
• Pharmacy Guide
• School of Medicine and Public Health Guide
• Undergraduate Guide
• Veterinary Guide

PhD in Biomedical Data Science

The current explosion of biomedical data, including Electronic Health Records, biomedical imaging, and genomics/proteomics/metabolomics, provide an opportunity to improve understanding of the mechanisms of disease and ultimately improve  health care. But fully harnessing the power of high-dimensional, heterogeneous data requires a new blend of skills including programming, data management, data analysis and machine learning.

Program Curriculum

The program blends the best of statistics, computer sciences, biostatistics and biomedical informatics. It gives students the training they need to make sense of large-scale biomedical data and to be scientific leaders in the team science that invariably accompanies such data. Unique features of the program include interdisciplinary training and research rotations mentored by program faculty.

Please refer the Graduate Guide for the most current program requirements

PhD Program Plan , a useful guide to help map out course scheduling

Core Topics

Three year-long course sequences (18 credits) will be selected from a set of core topics, including one biostatistics sequence (topics 1-2), and one computer science/informatics sequence (topics 3-6). The third sequence can be selected from any of the listed topics (topics 1-11).

Course requirements include additional credits of electives, which may be taken from the core topics (see above), or other graduate-level courses in biostatistics, computer science, or biomedical sciences. A students’ particular choices will be guided by and subject to the approval of their Academic Advisor.

Biology Training and Breadth

Students will generally specialize in some field of biomedical application (e.g., clinical medicine, genomics, or neuroscience). Thus, their training must include coursework in the biological sciences. In addition, students will need to meet the formal breadth requirements set forth by the Graduate School. These objectives will be achieved by selection of a minor (formal external or distributed), with the further requirement that this minor include at least six credits of biology courses (See list of potential Biology courses Biology Courses  to select from).

Research Ethics Requirement

All students will take a 1-credit Research Ethics course, preferably in Y1 and typically BMI 738 Ethics in Data Science, offered in the spring semester

Additional Requirements

In addition, to contribute to the students’ breadth of knowledge, to build cohesiveness among the students, to train the students in the critical evaluation of the biostatistical, computational, and scientific literature, and to build their professional skills, all students will participate in two year long seminar style courses in Y2 and Y3:

• Biodata Science Scholarly Literature (BMI 881-882, 4 credits): including readings, discussion, and presentations on a selected set of primary journal articles from the biostatistics, biomedical informatics, computer science, and biomedical literature. (taken in Y2)
• Biodata Science Profession Skills (BMI 883-884, 2 credits): covering such topics as giving scientific presentations, writing research grants, the publication process (writing scientific articles, reviewing such articles, and responding to reviewers), applying for jobs, employment opportunities in academics and industry, and working with scientific collaborators as part of interdisciplinary teams. (taken in Y3)

Research Rotations

Students will carryout three semester- or summer-long research rotations in the first year (fall-spring-summer terms) concerning a substantive problem in biomedical data science, advised by a Program Faculty member, in collaboration with an additional UW faculty member from the biological, biomedical, or population health sciences. The aim is for the students to begin to learn the craft of data science research, to expand their understanding of specific biomedical application areas, to gain a deeper exposure to a broad set of problems in biomedical data science, and to ultimately identify an appropriate advisor and to begin to identify a dissertation research topic. Please see the BDS_PhD_Rotation Policy  for details.

Prelim Exam

The PhD training includes an  Oral Preliminary Exam , ideally taken in the student’s third year, on a topic selected with the approval of the student’s advisor. A student is expected to have completed nearly all other course requirements by this time. Please see BDS PhD Prelim Exam Guidelines for details.

Dissertation

In addition, and in accordance with requirements set by the Graduate School at UW- Madison, students must pass a Final Oral Exam (i.e., a Dissertation Defense), following completion of their dissertation research. The primary requirement for the PhD degree is the completion of a significant body of original research and the presentation of this research in a dissertation. The research is carried out under the guidance of a member or members of the Program Faculty. The candidate must defend the dissertation in a Final Oral Exam. The rules for the composition of the Final Oral Exam committee are the same as for the Oral Preliminary Exam, except that, following Graduate School policy, the committee must have at least four members and at least one must be from outside the program.

The highly collaborative faculty in Biostatistics and Medical Informatics offer training to undergraduate, graduate and other students through a variety of flexible mechanisms aimed at attracting the best and brightest students into our innovative fields of quantitative methodology for biomedical investigation, and at training biomedical scientists in the optimal application of our methods to their chosen field of study.

For undergraduates, our summer programs offer the opportunity to gain a foundation in biostatistics or biomedical informatics and to explore research in these areas. Other undergraduates pursue honors work or research rotations with our faculty, either informally or as part of their major.

For students wishing to pursue Master’s or PhD level graduate work in quantitative methodologies in biomedical science, we offer both a  MS Degree Program in Biomedical Data Science   and a Doctoral Degree Program in Biomedical Data Science .

Other opportunities to train with our faculty are available through the graduate programs in Statistics ( Biostatistics Degree Option ) and in Computer Sciences, but also through graduate programs in Clinical Investigation, Genetics, and Population Health Sciences.

To learn more about our graduate and summer programs please contact:

Shelley Maxted (608) 263-4825 [email protected]

Beth Bierman (608) 265-8649 [email protected]

• PhD in Biomedical Data Science More
• MS in Biomedical Data Science More
• Biostatistics Degree Option for Statistics Students More
• BDS Graduate Student Handbook More
• Prospective Students More
• Summer Research Opportunity Program More
• BMI Course list More

Explore Our Department

Welcome to the department of biomedical data science.

The Department of Biomedical Data Science merges the disciplines of biomedical informatics, biostatistics, computer science and advances in AI. The intersection of these disciplines is applied to precision health, leveraging data across the entire medical spectrum, including molecular, tissue, medical imaging, EHR, biosensory and population data.

Our Mission

The Department of Biomedical Data Science (DBDS) is an academic research community, comprised of faculty, students, and staff, whose mission is to advance precision health by leveraging large, complex, multi-scale real-world data through the development and implementation of novel analytical tools and methods.

What is Biomedical Data Science?

Biomedical Data Science “spans a range of biological and medical research challenges that are data intensive and focused on the creation of novel methodologies to advance biomedical science discovery.” The term “data science” describes expertise associated with taking (usually large) data sets and annotating, cleaning, organizing, storing, and analyzing them for the purposes of extracting knowledge. It merges the disciplines of statistics, computer science, and computational engineering” ( Annual Review of Biomedical Data Science ).

DBDS Twitter Feed

Kristy Carpenter awarded NRSA F31 Diversity fellowship from NIGMS

The purpose of the NRSA Individual Predoctoral Fellowship to Promote Diversity in Health-Related Research (F31) fellowship award is to enhance the diversity of the health-related research workforce by supporting the research training of predoctoral students from population groups that have been shown to be underrepresented in the biomedical research workforce.

Congratulations, Kristy!

Biomedical Data Science (DBDS) Graduate Program

Our mission is to train future research leaders to design and implement novel quantitative and computational methods that solve challenging problems across the entire spectrum of biology and medicine.

NYU Center for Data Science

Harnessing Data’s Potential for the World

PhD in Data Science

An NRT-sponsored program in Data Science

• Areas & Faculty
• Admission Requirements
• Medical School Track
• NRT FUTURE Program

The Fall 2023 online application is now closed. The deadline to apply was Monday, December 12, 2022, 5pm ET.

Please find recordings of the phd medical school track information sessions on the open house webinars webpage ..

Students in the medical track will complete the  curriculum  for the PhD in Data Science program. Students in this track will be able to take electives offered at the NYU School of Medicine and to work with faculty at the school. The elective curriculum will be customized in consultation with the student’s mentors to optimally correspond to the research area and mentor chosen. Possible electives are listed below.

• Bioinformatics (BMSC-GA 2604) 
• Introduction to Health Informatics (BMSC-GA 4455) 
• Methods in Quantitative Biology (BMSC-GA 4449)
• Advanced Integrative Omics (BMSC-GA 4498)
• Deep Learning in Medicine (BMSC-GA 4493)
• Next Generation Sequencing Informatics (BMSC-GA 4452)
• Proteomic Informatics (BMSC-GA 4437)
• User Centered Design for Health Informatics (BMSC-GA 4483)
• Evaluation Methods for Predictive Risk Models (BMSC-GA 4499)
• Fundamentals of MRI (BMSC-GA 4404)
• Practical MRI 1 (BMSC-GA 4427)
• Practical MRI 2 (BMSC-GA 4428)
• Medical Imaging (BMSC-GA 4426)

Moreover, rotations will be offered with faculty at the School of Medicine.

School of Medicine Faculty

• Jakob Asslaender
• Sumit Chopra
• Krzysztof Geras
• Patricia Johnson
• Riccardo Lattanzi
• Daniel Sodickson

POPULATION HEALTH

• Yindalon Aphinyanaphongs
• Leora Horwitz
• Narges Razavian
• Michele Santacatterina
• Aristotelis Tsirigos

SYSTEMS BIOLOGY / GENETICS

• Aravinda Chakravarti
• Dafna Bar-Sagi

BIOINFORMATICS

• David Fenyo
• Kelly Ruggles

NEUROSCIENCE

• Gyorgy Buzsaki
• Eric Oermann

MEDICINE/CARDIOVASCULAR DISEASE

• Glenn Fishman

CDS Faculty

Data science.

• Kyunghyun Cho
• Carlos Fernandez-Granda
• Rajesh Ranganath
• Claudio Silva
• Andrew Wilson

Our use of cookies

We use necessary cookies to make our site work. We'd also like to set optional cookies to help us measure web traffic and report on campaigns.

We won't set optional cookies unless you enable them.

Cookie settings

Health Data Science

• Entry year 2024
• Duration Full time 3 - 4 years, Part time 4 - 7 years

The PhD in Health Data Science provides research training in developing applied informatic and analytic approaches to data within health-related subjects such as medicine and the biomedical, biotechnological, and bioengineering sciences.

You will join the programme with a supervisory panel composed of academics working in health data science more broadly. Throughout the programme, and particularly during your first year, you will be encouraged to engage in training opportunities at Lancaster and elsewhere to develop both your research skills and subject-specific knowledge and abilities. Throughout your studies, you will focus on novel scientific research, developing best practice in interpreting and communicating new scientific methods and findings.

Your department

• Lancaster Medical School Faculty of Health and Medicine
• Telephone +44 (0)1524 592032

Entry requirements

Academic requirements.

2:1 Hons degree (UK or equivalent) in a relevant subject.

We may also consider non-standard applicants, please contact us for information.

If you have studied outside of the UK, we would advise you to check our list of international qualifications before submitting your application.

Additional Requirements

As part of your application you will also need to provide a viable research proposal. Guidance for writing a research proposal can be found on our writing a research proposal webpage.

English Language Requirements

We may ask you to provide a recognised English language qualification, dependent upon your nationality and where you have studied previously.

We normally require an IELTS (Academic) Test with an overall score of at least 6.5, and a minimum of 5.5 in each element of the test. We also consider other English language qualifications .

If your score is below our requirements, you may be eligible for one of our pre-sessional English language programmes .

Contact: Admissions Team +44 (0) 1524 592032 or email [email protected]

Fees and funding

The tuition fee for students with home fee status is set in line with the standard fee stipend provided by the UK Research Councils. The fee stipend for 2024/25 has not been set. For reference, the fee stipend for 2023/24 was full-time £4,712.

The international fee for new entrants in 2024/25 is full-time £26,490.

Depending on the nature of the research project, an additional programme cost may be charged. This additional fee will contribute towards the costs incurred on specific research projects. These costs could include purchasing specialist consumables, equipment access charges, fieldwork expenses and payments for transcription/translation services.  Normally any additional charge will not exceed a maximum of £9,720 but this could be increased in exceptional circumstances.

Applicants will be notified of any specific additional programme cost when the offer of a place is made.

General fees and funding information

There may be extra costs related to your course for items such as books, stationery, printing, photocopying, binding and general subsistence on trips and visits. Following graduation, you may need to pay a subscription to a professional body for some chosen careers.

Specific additional costs for studying at Lancaster are listed below.

College fees

Lancaster is proud to be one of only a handful of UK universities to have a collegiate system. Every student belongs to a college, and all students pay a small College Membership Fee  which supports the running of college events and activities. Students on some distance-learning courses are not liable to pay a college fee.

For students starting in 2023 and 2024, the fee is £40 for undergraduates and research students and £15 for students on one-year courses. Fees for students starting in 2025 have not yet been set.

Computer equipment and internet access

To support your studies, you will also require access to a computer, along with reliable internet access. You will be able to access a range of software and services from a Windows, Mac, Chromebook or Linux device. For certain degree programmes, you may need a specific device, or we may provide you with a laptop and appropriate software - details of which will be available on relevant programme pages. A dedicated  IT support helpdesk  is available in the event of any problems.

The University provides limited financial support to assist students who do not have the required IT equipment or broadband support in place.

For most taught postgraduate applications there is a non-refundable application fee of £40. We cannot consider applications until this fee has been paid, as advised on our online secure payment system. There is no application fee for postgraduate research applications.

For some of our courses you will need to pay a deposit to accept your offer and secure your place. We will let you know in your offer letter if a deposit is required and you will be given a deadline date when this is due to be paid.

The fee that you pay will depend on whether you are considered to be a home or international student. Read more about how we assign your  fee status .

If you are studying on a programme of more than one year’s duration, tuition fees are reviewed annually and are not fixed for the duration of your studies. Read more about  fees in subsequent years .

Scholarships and bursaries

You may be eligible for the following funding opportunities, depending on your fee status and course. You will be automatically considered for our main scholarships and bursaries when you apply, so there's nothing extra that you need to do.

Unfortunately no scholarships and bursaries match your selection, but there are more listed on scholarships and bursaries page.

If you're considering postgraduate research you should look at our funded PhD opportunities .

We also have other, more specialised scholarships and bursaries - such as those for students from specific countries.

Browse Lancaster University's scholarships and bursaries .

Similar courses

Data, computing and communications.

• Communication Systems MSc by Research
• Communication Systems PhD
• Computer Science MPhil/PhD
• Computer Science MSc by Research
• Cyber Security MSc
• Cyber Security Executive MBA MBA
• Data Science MSc
• Data Science PgCert
• Data Science PgDip
• Health Data Science MSc

Health Studies

• Clinical Psychology DClinPsy
• Dementia Studies PhD
• Health Economics and Policy MSc
• Health Economics and Policy PhD
• Health Research PhD
• Mental Health PhD
• Organisational Health and Well-Being PhD
• Palliative Care PhD
• Public Health PhD

Mathematics and Statistics

• Mathematics PhD
• Natural Sciences MSc by Research
• Natural Sciences PhD
• Social Statistics PhD
• Statistics MSc
• Statistics PGDip
• Statistics PhD
• Statistics PhD (Integrated)
• Statistics and Epidemiology PhD
• Statistics and Operational Research MRes
• Statistics and Operational Research (STOR-i) PhD
• Anaesthesia and Peri-Operative Sciences PgDip
• Clinical Research MSc
• Clinical Research PgCert
• Clinical Research PgDip
• Medical Education PgCert
• Medical Ethics and Law PhD
• Medical Sciences MSc by Research
• Medicine PhD
• Medicine M.D.
• Social and Behavioural Sciences in Medicine PhD
• Sports and Exercise Sciences PhD

Important Information

The information on this site relates primarily to 2024/2025 entry to the University and every effort has been taken to ensure the information is correct at the time of publication.

The University will use all reasonable effort to deliver the courses as described, but the University reserves the right to make changes to advertised courses. In exceptional circumstances that are beyond the University’s reasonable control (Force Majeure Events), we may need to amend the programmes and provision advertised. In this event, the University will take reasonable steps to minimise the disruption to your studies. If a course is withdrawn or if there are any fundamental changes to your course, we will give you reasonable notice and you will be entitled to request that you are considered for an alternative course or withdraw your application. You are advised to revisit our website for up-to-date course information before you submit your application.

More information on limits to the University’s liability can be found in our legal information .

Our Students’ Charter

We believe in the importance of a strong and productive partnership between our students and staff. In order to ensure your time at Lancaster is a positive experience we have worked with the Students’ Union to articulate this relationship and the standards to which the University and its students aspire. View our Charter and other policies .

Why Lancaster?

League tables and reputation

A highly-ranked university with a global reputation.

Colleges and community

Your college will be your home away from home.

Careers and employability

Career support for our students through university and beyond.

Student life

Lancaster has so much to offer. On our campus, in our city and in our community, you’ll find your place – whoever you are.

Where is Lancaster?

Lancaster is easy to get to and surrounded by natural beauty.

The campus and the city

Our campus and the surrounding area is a great place to call home.

Your global experience

Build your global community on campus and around the world.

Wellbeing and support

Services to help you fulfil your potential at Lancaster.

Questions? Contact SACS enrollment management. [email protected]

Ph.D. Biomedical Data Science Program

Accredited degree programs Offered by Meharry Medical College, one of the nation’s oldest and largest historically black academic health science centers.

Live classes Engage in group discussions with professors and peers.

100% online Hands-on learning from anywhere.

4 year minimum Courses taken during fall, spring and summer semesters.

$ 37,800 Per year. Tuition is reviewed each year. Additional fees will apply.

Lead with data and improve health care and public health through our Biomedical Data Science Ph.D. program

Through biomedical data science, you can learn to analyze biomedical data to better understand diseases and provide improved – and more affordable — health care. In Meharry’s Biomedical Data Science Ph.D. program you will learn to discover new knowledge from biomedical data sets. You will collaborate with faculty, and conduct independent research, to develop new technologies and novel data analysis methods.

Biomedical Data Science Ph.D. curriculum and resources

We know that pursuing a doctorate program is one of the biggest career decisions you will make. The Biomedical Data Science Ph.D. will prepare you to develop novel tools and leverage real-world, massive biomedical data to advance precision health, drug discovery and other areas of biomedical science.

• Biomedical data science courses include predictive modeling, computational structural biology, applied machine learning, mathematical and statistical theory, advanced biostatistics and epidemiology.
• Research topics of interest before beginning your dissertation.
• First-class resources: high-performance, supercomputer network and robust, diverse data resources.

Work with faculty who are impacting society

Our faculty are impacting society through meaningful research in areas such as:

• Computational and theoretical biology, quantum computing
• Atomic, molecular, and protein modeling, e.g. for drug efficacy
• Population health informatics
• Geospatial big data to support health care related application scenarios
• Close-range photogrammetry, computer vision and 3D printing for health care and epidemiology

Scholarships available!  

As an HBCU, Meharry is committed to increasing diversity in the data science profession.

Meharry is committed to increasing diversity in the   data science profession.

Students admitted to attend the M.S. Data Science, or the M.S. or Ph.D. Biomedical Data are eligible for scholarships of up to 50 percent of tuition.

Your path to a Biomedical Data Science Ph.D.

Let’s talk

Just complete the form and we can schedule a time to discuss your goals and our programs.

Start your application. We are still here to help you along the way.

Develop expertise in biomedical data science and pursue impactful research.

Career Prep

Professional development services will help you take your next step after graduation.

• Board Members
• Working at OHT
• Antimicrobial Resistance
• Communicable Disease Dynamics
• Gender, Equity, and Livelihoods
• Health and Development
• Food, Climate, and Health
• Vaccines and Immunization
• OxygenForIndia
• Noncommunicable Diseases
• North America
• Nimai Valley

PhD in Data Sciences for Global Health

• Study Abroad Program
• Internship Program
• Weekly Digest
• Peer Reviewed Articles
• Infographics
• Presentations

OHT Advisors

How to apply.

The PhD program in Data Sciences for Global Health, jointly offered by BITS Pilani and the One Health Trust (OHT), offers training in global health issues and cutting-edge research methodology with rigorous fieldwork and data analysis. This program provides full-time, advanced education in global health plus expertise in qualitative and statistical/quantitative skills leading to an interdisciplinary degree. The BITS Pilani and OHT faculty have vast research experience in infectious disease dynamics, antimicrobial resistance, vaccines and immunization, environmental health, gender equity and livelihoods, health and development, health systems, and economics.

Students will spend part of their tenure in the program at the BITS Pilani campus and the other period housed at the Nimai Valley Center.

Applicant Brochure (2022–2023)

If you have any questions, please contact [email protected] .

Registration for the next cohort starting in January 2025 will open in August 2024!

Program Curriculum and Requirements

The students must complete six core courses covering three main subjects (24 credits) during the first year. Before the end of their second year, students will defend their thesis proposal and research plan. From their third year onwards, PhD candidates will present their work at seminars, conduct fieldwork, and communicate their research outcomes through research papers that will together form a PhD dissertation. Students must maintain a minimum grade of D and CGPA of 5.50 in all semesters. Each academic year will have two semesters.

First Year (first and second semester)

The first year will involve coursework in the following six core courses:

• Global Health I and II
• Data Sciences (including Research Methodologies) I and II
• Health Economics and Policy I and II

The coursework will help students build a strong theoretical foundation in global health and equip them with data skills. The first-year activities will take place on the BITS Pilani campus. A qualifying exam will be held at the end of the first year. Students will be promoted to the second year only if they pass at least two of their main subjects. The exam will include a written test and viva on the courses taught. BITS and OHT will jointly conduct the written exam and viva.

Second Year (third and fourth semester)

In the second year, students will draft a detailed research proposal to undertake thesis work and submit to their advisory committee for review. The students should take independent study/classes from faculty members from BITS-Pilani or OHT, in their research areas of interest (directed individual study), as they work on their research proposal and papers. A rotation method can be used to learn from various faculty members. Students are also encouraged to learn grant writing from their notional supervisor(s) and apply for research grants. At the end of each semester, students are expected to submit term papers, based on their research.

Students are strongly encouraged to find a potential advisor(s) during their second year. The main advisor will be from BITS Pilani and their co-advisor can be from OHT. Students will also choose a doctoral advisory committee (DAC) consisting of two members, from among the faculty members of BITS Pilani and OHT.

A candidacy/oral exam will be held at the end of the fourth semester. The exam will include an oral presentation on the research proposal developed in the second year. The proposal will be defended in the presence of a peer group and faculty of the concerned departments. Following the approval of the research proposal, students can then register for thesis units (maximum of 10 units per semester). A minimum of 40 thesis units should be completed to submit the thesis for examination.

Third Year through finishing the PhD program (fifth semester and beyond)

After advancing to Ph.D. candidacy, students are expected to present their progress at least twice each semester to their supervisors and DAC. Additionally, they are expected to submit progress reports to their respective DAC members at least once per semester. Students are also encouraged to present their research in seminars or conferences organized by BITS, OHT, and elsewhere.

• Field Work: Students are required to undertake field visits at OHT’s Nimai Valley Center. They may conduct quantitative or qualitative data collection corresponding to their research interests.
• Dissertation Defense: The student will prepare their thesis in consultation with their team of supervisors and present/defend to their DAC. They will be required to write three research papers, which will form their dissertation, and publish in peer-reviewed journals to graduate.

FIND OUT MORE

• Ramanan Laxminarayan
• Thomas P. Van Boeckel
• Deepshikha Batheja
• Geetanjali Kapoor
• Erta Kalanxhi
• Arindam Nandi
• Samantha Serrano

• Is there a fee to apply for this program?

The application fee is around INR 2,600. This is subject to revisions, and you can verify fees at https://www.bitsadmission.com/phdmain.aspx

• What is the application deadline?

The application deadline is typically in May-June with the semester starting in late July or early August. Intake for this program is yearly.

• Am I eligible to apply for this program?

We welcome applications from all professional, geographic, cultural, and socioeconomic backgrounds, with no age restriction. Meeting the minimum eligibility criteria does not guarantee admission into the program. For more information, please refer to the BITS PhD admissions prospectus.

Minimum eligibility criteria:

• ME/MTech/MPharm/MBA/MPhil/MSc/BE/BPharm or an equivalent degree: minimum of 60 percent aggregate
• MA: minimum of 55 percent aggregate
• MBBS/BDS/BVSc/MD/MDS/MVSc/BAMS/BHMS/BUMS/allied: minimum of 55 percent aggregate.
• My previous degree is from outside of India. What documents will I need to submit for registration if I am accepted?

International students will be required to provide an appropriate grade conversion to the Indian grading system, which has to meet the eligibility listed above. This will be in addition to the document checklist for the application package detailed in the BITS PhD admissions prospectus.

• Does the application process include an interview?

Shortlisted applicants will be interviewed about their knowledge of global health, data sciences, and research interests. OHT will participate in the interviewing panel. Given the diverse backgrounds of applicants, applicants are expected to be proficient in their previous degree(s) and have an aptitude for the other domains in the program. No written exam will be offered, but grades from previous degrees (transcripts), statements of purpose (SOPs), and letters of recommendation (LORs) will be considered.

• What is the expected time within which I can expect to receive a decision on my application?

You can expect to receive a decision on your application within six to eight weeks of the close of the application window.

• What is the expected length of the program?

All admitted candidates will be required to do the standard coursework in the first two semesters. Students must complete six core courses covering three main subjects (24 credits) during the first year. Before the end of their second year, students will defend their thesis proposal and research plan. From their third year on, PhD candidates will present their work at seminars, conduct fieldwork, and communicate their research outcomes through research papers that will write a PhD dissertation. PhD candidates must submit a thesis within five years to successfully complete the degree. For more information, please refer to the BITS PhD admissions prospectus. Students may take a maximum of seven years to finish their PhD due to unforeseen circumstances, with appropriate approvals from their dissertation committee.

• Is this an on-campus full-time program or a hybrid program?

This PhD is offered only as an on-campus full-time program. Students may be able to take courses online, which are offered at the other BITS campuses, as part of their degree requirements.

• Is it possible to change your supervisor after being assigned one at the time of offer of acceptance?

You will need to file a formal request for a change of supervisor and pending approval from an internal committee at BITS, you can change your assigned supervisor.

• What are the locations of the BITS Pilani campuses that offer courses applicable to this program?

You can find the addresses for each campus below:

BITS Pilani, Hyderabad Campus

Jawaharnagar, Shamirpet Mandal Medchal-Malkajgiri District Hyderabad 500078 Telangana

Google Maps

BITS Pilani, Goa Campus

NH 17B, Bypass, Road Zuarinagar, Sancoale Goa 403726

BITS Pilani, Pilani Campus

Vidya Vihar Pilani Rajasthan 333031

• What is the fee structure for this program?

The following are the details of the fees in INR payable by all students admitted to the PhD Program in the academic year 2025-2026 at BITS- Pilani, Pilani Campus.

* Payable at the time of admission; # Payable at the time of thesis submission

Financial Assistance:

Full-time PhD students admitted into the PhD program are eligible to be considered for a fellowship of INR 34,000/- or INR 37,000/- per month as per intake qualifications. Consideration for a fellowship will be as per institute norms, details of which are available in the PhD brochure on the admission website. It will be obligatory on the part of every admitted full-time student to undertake eight hours (per week) of work as assigned to her/him by the institute.

• What are the potential sources of financial assistance given to PhD students?

All successfully admitted students will have financial support through one of the following sources:

• Self-funded fellowships such as UGC/CSIR NET JRF , DBT JRF/SRF , ICMR JRF/SRF , DST Inspire
• A BITS Pilani Fellowship, which will include working as a teaching assistant (TA). The stipend/scholarship is in lieu of the TA duties.
• What is the expected stipend?

All admitted students who do not have self-funded fellowships will receive a BITS Pilani Fellowship of INR 34,000/month during the first year, provided for up to five years from the date of admission. It can be enhanced to INR 37,000 per month from the second year on and to INR 40,000/42,000 per month in the third year, based on the student’s performance and output. The fellowship amount is usually aligned with the norms of the Government of India.

• If I have a self-funded fellowship such as JRF/SRF, will I still be expected to have teaching duties on the BITS campus?

Yes, you will still be required to carry out teaching assistant (TA) duties every semester you are enrolled in the program.

• As part of being a teaching assistant (TA), how many hours of classes am I expected to assist in a week?

On an average, approximately 8 hours a week.

• Does OHT provide research assistantships (RA) to complement the stipend?

Yes, OHT provides research opportunities to PhD students to earn additional income on top of their stipend.

• Does BITS or OHT provide on-campus accommodation?

Students will be expected to be at one of the BITS campuses in their first year. From the second year onwards, students are encouraged to spend time on one of the BITS campuses or OHT India campus, depending on their research area of interest. OHT will be able to provide housing on campus (expected completion: 2024/2025). Students are expected to cover their cost of stay/living at both institutions.

• Can PhD students live off-campus and attend classes?

Yes, PhD students can live off-campus and commute with their own vehicles or any other available public modes of transportation.

• Is there any accommodation for TAs assisting classes remotely?

There usually is no provision for such requests. However, temporary accommodations can be discussed on a case-by-case basis.

• Are there any qualifier exams to confirm one’s candidature as a PhD student? Are multiple attempts of the exam allowed?

Yes, apart from the semester exams for the courses a candidate is taking, candidates are expected to pass two qualifier exams to maintain their candidacy as a PhD student. Students are expected to choose a primary and a secondary research area for their thesis and to write qualifier exams in these areas. The areas can be from two different departments. The candidate should consult the DRC (Departmental Research Committee) to know about the areas offered and the exam modalities. Every student has until the end of the second year to appear for and clear their qualifier exams. A maximum of two attempts are allowed to clear qualifier exams and both the areas must be cleared together.

Eligible students may apply for the PhD program in Data Sciences for Global Health, from August 2023 – January 2025. Online application forms will be available from December 2023 to August 2024. The number of students admitted will vary based on the availability of positions in the department, funding, and the merit of applicants.

Applications to the PhD program are invited from candidates with a master’s degree in any basic science or liberal arts discipline. We also accept applications from candidates with a bachelor’s degree in medical, dental, veterinary, pharmaceutical, or alternative health sciences and engineering. Applicants from other fields are also encouraged to apply.

The minimum eligibility requirements for admission are as follows:

• ME / MTech / MPharm / MBA / MPhil: minimum of 60% aggregate
• MSc / BE / BPharm or an equivalent degree: minimum of 60% aggregate
• MA: minimum of 55% aggregate
• MBBS / BDS / BVSc / MD / MDS / MVSc / BAMS / BHMS / BUMS / allied

Applicants should submit the following:

Statement of research purpose (maximum two pages), indicating the candidate’s academic background, broad research interests, career goals, and how a PhD in Data Sciences for Global Health from BITS Pilani–OHT will advance their career goals.

Two letters of recommendation

The shortlisted applicants will be interviewed about their knowledge of global health, data sciences, and research interests. OHT will participate in the interviewing panel. There will be no written exam, but grades from previous written exams will be considered.

If you have any questions, please contact  [email protected] .

Invest in a better planet for future generations. Support our work to fight drug resistance, prevent disease spillovers, and improve pandemic preparedness.

Stay Informed

Too busy to keep up with the latest scientific literature in global health? Let us summarize it for you with our weekly digest. Sign up here.

Privacy Overview

• Visit the Gateway
• Visit the Alliance
• Visit HDR UK Futures

HDR UK-Turing Wellcome PhD Programme in Health Data Science

This truly outstanding and generously funded four-year programme at top UK universities provides you a pathway to join the UK’s leaders in health data research.

What this unique PhD programme offers you

Four-year programme: An initial foundation year allows students to gain real experience and insight into health data research.

Hosted by leading universities: Our host universities are among the very best in health data research.

Nurturing each student: Our programme aims to identify the particular abilities and interests of each student, and gear their PhD experience to effectively develop them.

Leadership Programme: Students benefit from a bespoke expert-led programme to develop the skills they need to understand, collaborate and influence others.

Generous funding: Students have their tuition fees (UK Home rate), college fees (where applicable), research expenses and travel costs paid and receive an enhanced, tax-free stipend with increases every year. (Y1 outside London: £23,955, Y1 in London: £25,954)

Building networks and experience: We actively support students in building networks and contacts in academia, the NHS and industry as well as taking internships and other opportunities to gain real-world experience. This includes a post-PhD bursary to support your next career step.

Team spirit: Strong relationships are built between our entire cohort of students through joint activities that build a genuine team spirit.

Personal support:  Each student has their own Director of Studies who is an additional point of contact during their time with us. All students are also further supported by the PhD team.

“The PhD programme has enabled me to gain first-hand experience in modern health data science approaches. It’s a truly unrivalled opportunity.”  Steven Wambua

Who is the PhD programme for?

We recruit enthusiastic, talented students who want to use data-driven research to develop and shape the UK’s response to the most complex health challenges of our times.

Applicants must have (or be on track to obtain):

• A first class or 2:1 undergraduate degree in statistics, mathematics, computer / data science, physics or an allied subject  or
• Another undergraduate degree subject and outcome but can demonstrate their suitability for this programme through additional qualifications or research experience.

Active or currently registered health care professionals   are not eligible and should consider the Wellcome PhD Fellowships for Health Professionals .

Applicants also need to meet the following criteria:

• Successful admission to the specified degree programme at one of our partner universities. Students will be expected to meet the admissions requirements of that department and university but do not need to hold the offer at the point of application.
• Two satisfactory academic or relevant references.
• Proof of a legal right to study in the UK or ability to satisfy the current requirements of UK Visa and Immigration.

Training is in-person, hybrid and virtual throughout the first year.

We are committed to a diverse and inclusive research culture . We welcome those who are returning from the workplace, international candidates and everyone underrepresented in STEM and academia. For further details see our FAQs .

We cannot accept applicants who are looking for a part-time PhD or those who are aiming to study whilst continuing to be employed elsewhere.

We aim to accommodate specific needs and personal circumstances. Please make us aware of individual circumstances when applying or contact us directly at  [email protected] . Please note our  applicant privacy notice .

If you have questions or require adjustments to the application process, please contact us below via email or telephone (+44 (0)770 847 8846).

There are no nationality restrictions and international students are able to apply. However, applicants are advised the award only covers fees at the UK/Home level. International students will be required to secure an additional scholarship from Queen’s University Belfast (after receiving a offer from us at interview) to cover the difference between Home and Overseas fees. This will limit the university choices available:

(Please be aware that these are usually highly competitive and will need to be applied for separately in your application to Queen’s University Belfast post-offer. A successful application to the PhD programme does not guarantee a fee waiver or scholarship. We do not accept applications from candidates who are self-funding.)

We are currently only recruiting for Queen’s University Belfast.

These are only initial programmes of study for Year 1. Students may transfer to a new university programme from Year 2 after research projects have been confirmed.

Is this the PhD future for you?

Watch our Applicant Open Day hosted by our current students to find out more about the programme and whether it’s for you.

Applications are currently: Closed

The application process.

Details required:

• Contact details
• Details and transcripts of university qualification(s)
• Any relevant job history
• Answers to personal-statement type questions (250-words maximum for each answer)
• Contact details for two referees
• There is no need to apply to the university, submit a research proposal, provide IELTS scores or contact supervisors at this stage

Submitted applications will first be checked for eligibility and then will undergo a first stage review. This will involve triage by the PhD Team in April 2024 . Successful applicants will be invited to an interview in May 2024 .

After receiving an offer, applications will be invited to apply to Queen’s University Belfast.

Selection criteria

Applicants should demonstrate that they meet the following criteria:

* These criteria will be assessed at interview via a pre-interview exercise.

HDR UK reserves the right to reject applicants who do not meet the criteria at any stage. Regretfully, we can only provide feedback for candidates who reach interview.

Programme Structure

The four-year programme is divided in two. There is an initial Foundation Year followed by a three-year research project. The first year combines the best in university-based training with HDR UK-led national activities. And we support students to produce game-changing research plans and their projects are backed by substantial research funding.

Foundation year

3-5 day immersion events allow students to gain insight into the work of HDR UK, and our academic, clinical and industry partners. Courses may be residential (expenses provided) with up to a week away from their home university or online. Students undertake an intensive deep dive into an important area of health data science. Immersion topics include risk prediction, oncology, clinical trials, epidemiology and bioinformatics. Past immersion weeks have been hosted by the Universities of Birmingham, Manchester, Oxford and University College London and the European Bioinformatics Institute.

The immersion events encourage students to work together and stimulate new interactions:

• Axes of Prognosis
• The Different Facets of Data

Research areas

PhD research projects can be linked to The Institute’s:

• Research priorities
• Research hubs
• Partnerships

Team working

Students operate as a national cohort and work collaboratively with others, overcoming traditional institutional silos. Students are registered with a  partner university  but can draw on academic expertise from across the HDR UK network and are supported to formulate research activities that bring together experts from across the UK.

• You can contact us at [email protected]   or phone (+44 (0)770 847 8846). 
• For details of how we process applicants’ data see PhD Applicant Privacy Notice .

Students have access to graduate-level courses and research project rotation in their university to introduce them to different areas of health data science and enable them to develop a bespoke research project under the guidance of our expert university leads.

Regular workshops and short courses introduce students to the work of HDR UK experts across our hubs, themes and priority areas and to external organisations. Past contributors have included NHSX, IQVIA and AstraZeneca.

Immersion and workshop events allow students to better understand the wider health and social care landscape and accelerate their potential to become sector leaders. They also enable students to develop more ambitious PhD research projects by stimulating collaboration with external academics, industry-based organisations, or by using national data infrastructure.

Training is provided by academic, industry and NHS experts to promote personal and professional development in leadership capability, cross-sector collaborative skills and inter-disciplinary working. In particular, HDR UK is committed to working with public and patients to build increased trust in health data research as well as designing solutions focused on improving patient outcomes and experience. Students will develop communication and collaborative skills to help put them at the forefront of this mission.

At the end of the Foundation Year students design a bespoke three-year research project and a multi-disciplinary supervision team based on their training experiences.

Research proposals will be rigorously reviewed by expert academics and public-patient representatives to ensure they are of the highest standards in terms of ambition, scientific methodology and impact on patient outcomes.

The research will be carried out at their home university and could be linked to HDR UK  research priorities ,  research hubs  or  partnerships .

This includes short immersions plus  longer practical real-world projects with businesses and other organisations at the cutting edge of everything from medical devices, to life sciences, to vaccines. Students also learn about leadership theory and attend specially-convened seminars from senior figures in relevant areas of healthcare.

Networks and experience: Students will be actively supported in building networks and contacts in academia, the NHS and industry as well as taking internships and other opportunities to gain real-world experience.

Team working: Students operate as a national cohort, building strong relationships through joint activities and overcoming traditional institutional silos.

Workshops: Regular workshops and short courses introduce the work of HDR UK experts and to external organisations.

Immersion events: These allow students to better understand the wider health and social care landscape and accelerate students’ potential to become a sector leader. They also enable them to develop an ambitious PhD research project.

Researcher development: Training is provided by academic, industry and NHS experts to promote personal and professional development in cross-sector collaborative skills, communication and inter-disciplinary working.

“Our Leadership Programme will give PhD students the chance to develop the practical skills they need to bring people together to use health data science to deliver much-needed innovations and advances in health and care,”  Professor Peter Bannister

Our partners

Programme partners include NHS Digital, AstraZeneca, Moorfields Eye Hospital NHS Foundation Trust, and University Hospitals Birmingham.

More broadly it will work with winners of the NHSX AI Innovation Award , which funds and supports promising artificial intelligence technologies in health and care. There will also be opportunities with businesses on the DTI listed top 100 digital health innovators which are using big data for healthcare innovation.

Master’s Degree Scholarships

We offer 10 annual Master’s degree scholarships worth £10,000 for students with an interest in dementia or diabetes research.

Undergraduate Summer Internship in Health Data Research

Apply for a summer work placement in health data research at a UK research organisation, with an HDR UK-Wellcome Biomedical Vacation Scholarship

Join the HDR UK Alumni Network

HDR UK’s online Alumni Network brings together the amazing people who have been part of our training and education programmes.

Our host universities

- - - - Meet our PhD students

Our PhD students come from a wide range of backgrounds - discover who they are and what their experiences have been as part of the PhD programme

Meet the PhD Programme team

Our wider team consists of leading experts in disciplines including theoretical physics, computer science, mathematics and statistics, applied mathematics and biochemistry.

• Miguel Bernabeu – University of Edinburgh
• Ioanna Manolopoulou – University College London
• Niels Peek – University of Manchester
• Iain Styles – Queen’s University Belfast
• Paul Taylor – University College London
• Catalina Vallejos – University of Edinburgh
• Angela Wood – University of Cambridge
• David Wong – University of Manchester
• Tom Nichols – University of Oxford
• Magnus Rattray – University of Manchester

Data Science Specialization

The Data Science Option is designed to meet a critical educational gap at the intersection of Biomedical & Health Informatics (BHI) and Data Science.  This option, as an elective part of our research MS and PhD program s, provides students an introduction to the world of data science, giving them the skills with a variety of techniques and tools. The goal of this option is to provide students the opportunity to acquire a strong foundation in data science, so they may apply those methods and techniques to current BHI research and to further their careers. This option is aligned with the campus-wide  eSciences Institute graduate-level educational offerings.

Regular Data Science Option:

To complete the regular data science option, students must pass

• At least one course from each of the following three areas: (1) Software development for data science, (2) Statistics and machine learning and (3) Data management and data visualization. Courses in each of these categories are listed in the BHI graduate resources page.
• Two quarters of the eScience Community Seminar  (1cr each quarter).

Advanced Data Science Option:

For students with a strong computer science background, or for those who want a more intensive experience, we also allow for the Advanced Data Science Option . In alignment with the eSciences Institute , those requirements are:

• CSE 544 (4cr)– Principles of Data Management
• CSE 546 (4cr)/STAT 535 (3cr) – Machine Learning
• CSE 512 (4cr) – Data Visualization
• STAT 509 (4cr)– Econometrics I; Intro to Mathematical Statistics or STAT 512 (4cr)-513 (4cr) (a more in-depth version of 509,4cr)
• Four quarters of the eScience Community Seminar.

Upcoming Events

PhD in Biomedical Informatics

The PhD program in Biomedical Informatics is part of the   Coordinated Doctoral Programs in Biomedical Sciences . Students are trained to employ a scientific approach to information in health care and biomedicine. Students may only enroll full-time, as required by the Graduate School of Arts and Sciences (GSAS). The first two years are generally devoted to coursework and research. Subsequent years focus on independent research that culminates in a dissertation. 

Our PhD students come from top universities in the country and around the world. The group is dynamic and engaged, breaking new ground in informatics research as evidenced by their strong publication records. Our students are highly collaborative, frequently assisting on each other’s projects, sharing ideas, and supporting each other.

The program consists of core courses that are required of every student and provide a foundation in general biomedical informatics methods, techniques and theories, while electives enable students to apply these methods to one or more areas of specialization in bioinformatics, translational, clinical informatics, clinical research informatics, or public health informatics. In addition, students conduct research, assist in teaching (if PhD or postdoctoral trainees), and attend colloquia.

Degree Requirements

​ Courses : A minimum of 60 points of Columbia University graduate (4000 level or above) coursework, 6 residence units, consisting of:

• Research each term (BINF G6001, BINF G9001)
• 5 core classes
• 2 domain (specialization) courses
• 3 educational objectives courses
• 1 ethics course (spring term of first year)
• serving as a TA for 2 classes (or 1 class for MD-PhD students)
• 1 research seminar each term

Students must complete a minimum of 60 points of Columbia University instruction at the 4000 level or higher, address any admission deficiencies, and complete DBMI degree requirements. In years three and above, research is the primary focus of the student’s degree program, and the number of hours spent on research increases with each year in the program. Students enroll in BINF G6001 fall and spring terms as follows: a) 6 points each term year one, 9 points each term year two, 12 points each term years three and above. Students enroll in BINF G9001 in lieu of BINF G6001 the term following successful completion of the Oral II/Depth Exam. In their final term of enrollment, students will also register for BINF G9999 Doctoral Dissertation for 0 points. Students should pursue five goals when conducting research, and the grade earned in the required research classes (BINF G6001, BINF G9001) will reflect how well the student has achieved these goals: 1) understand the nature of informatics research 2) master intellectual and technical skills necessary for research 3) read and apply the scientific literature, 4) develop skill in scientific writing 5) demonstrate a responsible working attitude.

Ethics:  PhD students are required to enroll in CMBS G4010 Responsible Conduct of Research and Related Policy Issues in their second term in the program.

Teaching Assistantship: Students are required to serve as teaching assistants (TAs) for two courses in the department. In order to earn credit for TA responsibilities, students need to register for two points of BINF G8010 MPhil Teaching Experience each semester in which they serve as a TA. Students and faculty are solicited in spring term for their top 3 preferences. The Training Committee assigns TAs based on faculty and student preferences and departmental needs. The assignments will be communicated to students and faculty by the Graduate Program Manager. PhD students are required to TA two courses. Two-year postdoctoral research fellows TA one course; three-year postdoctoral research fellows TA two courses. MD-PhD students TA one course.

Seminar: PhD students are required to enroll in the weekly DBMI seminar. PhD students in the bio track are required to enroll in the DBMI seminar in their first year in the program, and may substitute the Systems Biology seminar in year 2 and beyond.

Residence Units: PhD students accrue 6 residence units for the degree. They are enrolled in the appropriate residence unit category by the GSAS Office of Graduate Affairs every fall and spring term.

Milestones: There are four milestones for PhD students:

• Breadth Exam
• Dissertation Proposal
• Dissertation Defense

Academic progress is tracked each semester by the students and their academic advisors (see Forms page for semester forms)

Research Rotations With the exception of MD-PhD students whose research rotation occurs between years 1 and 2 of medical school, all PhD students rotate in two different research labs their first year. Research rotations begin by the end of the change of program (add/drop) period of each term. The second research rotation begins the first day of classes of spring term. Projects should be completed prior to the start of the subsequent term. The permanent research advisor is chosen by May 15 of the first year. The Training Committee grants final approval of research rotations and permanent research advisor selections. Work with the permanent research advisor commences the next business day following the last day of final exams. A third summer rotation is possible with the Committee’s permission.

For first year students rotating with different research advisors, the Fall term dates for the first research rotation of BINF G6001 are the second week of September through the MLK, Jr. Holiday. For Spring term, the dates are the day following the MLK, Jr. holiday (the first day of classes) until the last date of final examinations ( see the online University academic calendar ) .  Work with the permanent research advisor commences the next business day following the last day of final exams.

Rotation Research Advisor Prior to the start of the Fall and Spring semesters, first-year PhD students should contact the faculty with whom they are considering doing a rotation to request an appointment. Selection of a research rotation advisor must be official by the end of the drop/add period of each semester. Students should discuss expectations for the rotation as well as a finite project to be completed by the end of the term of the rotation with the research advisor. This prevents projects continuing into the next semester which impacts the output of the new research rotation. The project should not depend on applying for a new IRB as this will delay the research into the subsequent semester, which is ill-advised. The Training Committee grants final approval of research advisors.

Register for research credit and a letter grade (6 points in fall and spring of first year, 9 points in fall and spring of second year, 12 points in fall and spring all subsequent years).

Publications PhD students and postdoctoral fellows are expected to make submissions to publications and conferences each year. The frequency and appropriateness of these submissions are decided by the research advisor. No student or fellow may submit work to any publication or conference without the expressed prior approval of their research advisor. Prior to submission, the research advisor must review final versions of all papers and abstracts submitted to journals, conferences, books or other publications. This policy applies to all publications, regardless of authorship, that deal with work that has been done at DBMI, Columbia University, or any affiliated institution(s).

Funding More information about funding sources and fellowships is available in the Student Funding page .​

Skip to content

Read the latest news stories about Mailman faculty, research, and events. 

Departments

We integrate an innovative skills-based curriculum, research collaborations, and hands-on field experience to prepare students.

Learn more about our research centers, which focus on critical issues in public health.

Our Faculty

Meet the faculty of the Mailman School of Public Health. 

Become a Student

Life and community, how to apply.

Learn how to apply to the Mailman School of Public Health. 

Public Health Data Science

The MS in Biostatistics Public Health Data Science Track (MS/PHDS) is designed for students interested in careers as biostatisticians applying statistical methods in health-related research settings. The MS/PHDS Track provides core training in biostatistical theory, methods, and applications, but adds a distinct emphasis on modern approaches to statistical learning, reproducible and transparent code, and data management. It is an appropriate program for students who intend to conclude their studies with the MS degree as well as those who want to pursue a PhD in biostatistics

All MS/PHDS candidates begin their studies in the fall semester. The length of the MS/PHDS program varies with the background, training, and experience of the candidate, but the usual period needed to complete the 36 credit MS/PHDS degree is two years (four semesters). In addition to fulfilling their course work, all MS/PHDS students also complete a one-term practicum and capstone experience.

Competencies

Through a curriculum of 36 credit hours of course work, a practicum, and the capstone experience, the MS/PHDS track provides students with the skills necessary for a career as a public health data scientist and a rigorous grounding in traditional biostatistics.

In addition to achieving the MS in Biostatistics core competencies, students in the PHDS Track gain the following specific competencies in the areas of public health and collaborative research, the foundations of applied data science, teaching biostatistics and biostatistical research. Upon satisfactory completion of the MS/PHDS, graduates will be able to:

Public Health and Collaborative Research

• Formulate and prepare a written statistical plan for analysis of public health research data that clearly reflects the research hypotheses of the proposal in a manner that resonates with both co-investigators and peer reviewers;
• Prepare written summaries of quantitative analyses for journal publication, presentations at scientific meetings, grant applications, and review by regulatory agencies;

Foundations of Applied Data Science

• Develop expertise in one or more statistical software and database management packages (often R and SQL, among others) routinely used by data science professionals;
• Implement a reproducible workflow for data analysis projects, including robust project organization, transparent data management, and reproducible analysis results;
• Develop and execute analysis strategies that use traditional statistical tools or modern approaches to statistical learning, depending on the nature of the scientific questions of interest;
• Identify the uses to which data management can be put in practical statistical analysis, including the establishment of standards for documentation, archiving, auditing, and confidentiality; guidelines for accessibility; security; structural issues; and data cleaning;

Teaching Biostatistics

• Review and illustrate selected principles of study design, probability theory, estimation, hypothesis testing, statistical learning, and data analytic techniques to public health students enrolled in introductory level graduate public health courses; and

Biostatistical Research

• Apply probabilistic, statistical, and data scientific reasoning to structure thinking and solve a wide range of problems in public health.

Course Requirements

MS/PHDS graduates are expected to master the mathematical and biostatistical concepts and techniques presented in the curriculum’s required courses. Each student's program is designed on an individual basis in consultation with a faculty advisor taking into consideration the student's prior educational experience.

Students who have mastered an academic area through previous training may have the corresponding course requirement waived. Some students, such as those with undergraduate majors in statistics or mathematics, may apply to have several courses waived. Students wishing to waive one or more courses must request approval in writing from their advisors and the Director of Academic Programs. These students must still complete a minimum of 36 points to earn the MS/PHDS degree.

Required Courses

Below is the required course work. Students consult their faculty advisors before registering for classes to plan their programs based on their individual background, goals, and the appropriate sequencing of courses. Waiver of any required courses (with prior written approval of their faculty advisor and the Director of Academic Programs) enables students to take other, higher level classes.

*Students who have strong math background and/or have taken basic machine learning methods, can substitute the P8106 Data Science II with P9120 Topics in Statistical Learning and Data Mining I. 

Students choose four or more courses from the list below or from alternatives approved by their academic advisors.

Sample Timeline

Below is a sample timeline for MS/PHDS candidates. Note that course schedules change from year to year, so that class days/times in future years will differ from the sample schedule below; you must check the current course schedule for each year on the course directory page .

Practicum Requirement

One term of practical experience is required of all students, providing educational opportunities that are different from and supplementary to the more academic aspects of the program. The practicum may be fulfilled during the school year or over the summer. Arrangements are made on an individual basis in consultation with faculty advisors who must approve both the proposed practicum project prior to its initiation, and the report submitted at the conclusion of the practicum experience. Students will be required to make a poster presentation at the department’s Annual Practicum Poster Symposium which is held in early May.

Capstone Experience

A formal, culminating experience for the MS degree is required for graduation. The capstone consulting seminar is designed to enable students to demonstrate their ability to integrate their academic studies with the role of biostatistical consultant/collaborator, which will comprise the major portion of their future professional practice.  

As part of the seminar, students are required to attend several sessions of the Biostatistics Consulting Service (BCS). The Consultation Service offers advice on data analysis and appropriate methods of data presentation for publications, and provides design recommendations for public health and clinical research, including preparation of grant proposals. Biostatistics faculty and research staff members conduct all consultation sessions with students observing, modeling, and participating in the consultations.

In the capstone seminar, students present their experience and the statistical issues that emerged in their consultations, developing statistical report writing and presentation skills essential to their professional practice in biomedical and public health research projects.

Paul McCullough Director of Academic Programs Department of Biostatistics Columbia University [email protected]

• See us on twitter
• See us on instagram
• See us on facebook

Clinical Data Science Fellowship

A full-time one-year post-doctoral training fellowship (with possibility of a one-year extension) for PhDs and MDs to bridge the gap between data science and clinical medicine. Fellows will receive full salary support from the program. The focus of the program is to immerse fellows in interdisciplinary research and clinical workflows so they can learn, build and deploy real-world health data solutions. The fellowship will be self-directed and project-based, with top researchers and clinician mentors.

Program Details

Fellow Background : Ideal fellows are highly motivated, detail-oriented individuals with experience in genome data analysis, large-scale data visualization, artificial intelligence and machine learning. They will join a cohort developing computational tools and services for the analysis, modeling and management of biomedical data in patient care. Fellows will be responsible for building, modeling and testing algorithms and visualization tools informing the clinical management of patients from large-scale clinical laboratory datasets and patient electronic medical records. Competitive applicants will include individuals from varied training backgrounds, such as medicine, biosciences, engineering and computer science. Fellows with strong computational, analytical and statistical training and bioinformatic and machine learning backgrounds are preferred. A PhD or MD is required.

Committee Structure : Fellows will be assigned to a data science mentor and a clinical mentor that they will interact with on a daily basis. Fellows will rotate with their clinical mentors to understand operational clinical workflows, infrastructure, unmet needs and opportunities for innovation. Fellows will then work in collaboration with their data science and clinical mentors to prototype and develop health technology solutions for clinical deployment.

Program Timeline : During the first week of the program, fellows will participate in group discussions with healthcare and data science experts to establish a foundational understanding of concepts, principles and challenges in clinical care. During this time, fellows will learn about common tools and methods for healthcare data analysis, and will begin to brainstorm potential fellowship projects. Fellows will then rotate and embed themselves within the practice of their clinical mentor. The remainder of the year will be spent collectively with their data science and clinical mentors, working on their projects. At the completion of their first fellowship year, fellows may be able to extend their training for another year, pending availability of a specific data science research mentor. Monthly joint seminars with other fellows, and their clinical and data science mentors, will serve as key opportunities to present project ideas and updates, and solicit feedback from the larger group.

Project Examples : Fellows will work with an interdisciplinary group of researchers, data scientists, clinicians and product developers to build tools and services for a learning-based healthcare system, supporting clinicians and improving patient outcomes. The purpose of this collaborative effort is to address gaps in domain knowledge, remove isolated data silos and understand important clinical challenges, fostering effective interdisciplinary partnerships between experimental and quantitative biologists and healthcare providers. Examples of potential projects include:

• Healthcare Analytics : Mine electronic healthcare record information to develop learning-based clinical decision support tools and improve clinical management and patient outcomes.
• Genomics : Perform prospective and retrospective analyses of clinical sequencing data to build predictive models of cancer patient mutational signatures and disease relapse.
• Quantified Self : Development of tools to integrate personal health sensor data from mobile phone applications and wearables with routine laboratory testing values to better track overall health, early disease diagnosis and disease progression.
• Clinical Trials and Drug Development : Development of analytical models to identify and target specific populations for clinical trials and novel drug development.

Foreign Students & Visa Sponsorship

Canadian visa requirements.

Graduates of Canadian medical schools will be placed on ECFMG sponsored J-1 visas. They are not required to take the qualifying examinations such as FMGEMS, NBME, and USMLE in order to obtain their visas.

Note: At this time, the government of Canada is restricting approval of physicians wishing to obtain clinical training outside Canada. SHC is unable to obtain a J-1 visa without the consent of the Canadian government.

Non-Canadian Visa Requirements

All trainees in residency and clinical fellowship programs will be placed on ECFMG sponsored J-1 visas.

Stanford Hospital and Clinics (SHC) does not sponsor such trainees for the H-1B visa. ECFMG requires a valid ECFMG certificate obtained by successful completion of their qualifying examinations (VQE, FMGEMS, NBME, or USMLE) coupled with the appropriate English language examination to be eligible for a visa.

Allow 120 working days for ECFMG to process an initial visa.

For further information, please contact: Educational Commission for Foreign Medical Graduates 3624 Market Street Philadelphia, PA 19104-2685  Tel: (215) 386-5900

We are now accepting new applications for the Clinical Data Science Fellowship for a flexible start date of July-December 2023. Please submit all application material listed below by May 1, 2023.

Required Materials

We invite eligible applicants to submit:

• A single-page letter of intent addressing your interest in the program, your relevant qualifications and training, and relevant prior projects and research.
• Updated Curriculum Vitae (CV)
• Your citizenship, residency, and or visa status.

Please submit all materials and letters electronically (pdfs) by May 1, 2023 to:

Vivek Charu, MD, PhD Assistant Professor of Pathology (Quantitative Sciences) Assistant Director, Clinical Data Fellowship Program Email: [email protected]

Current Clinical Data Science Fellows

Laura Symul, PhD

Clinical Data Science Interests: Digital Medicine, Menstrual Health, Multivariable time-series analysis, Biological modeling

Rohan Joshi, MD, PhD

Clinical Data Science Interests: Clinical genomics, Machine learning for multimodal medical data, Causal inference

Roozbeh Dehghannasiri, PhD

Clinical Data Science Interests: Bioinformatics, Statistical Learning, High-Dimensional Data Analysis, Cancer System Biology

Clinical Data Science Fellows Alumni

Jessica Chen, PhD

Clinical Data Science Interests: Clinical Genomics, Healthcare Analytics, Drug Discovery

Haik Kalantarian, PhD

Clinical Data Science Interests: Ubiquitous Computing, Wearables, Sensors

Nick Haber, PhD

Clinical Data Science Interests: Artificial Intelligence, Active Learning, Ubiquitous Computing

Riyika Yamashita, MD, PhD

Interests: Machine/Deep Learning for Biomedical Data (Radiology, Pathology, Genomics), Clinical Decision Making, Causal Inference, Dataset Bias

• Accessibility Tools
• Current Students
• Postgraduate
• Postgraduate Research Programmes
• Medical School Postgraduate Research Courses

Population and Health Data Science, Ph.D.

• An introduction to postgraduate study
• Postgraduate Taught Courses
• Postgraduate scholarships and bursaries
• Contact the Postgrad Admissions team
• Scholarships and Bursaries
• Research projects
• Postgraduate Research Programmes coming soon
• How to apply for your Postgraduate Research programme
• School of Aerospace, Civil, Electrical and Mechanical Engineering Research Courses
• School of Biosciences, Geography and Physics Postgraduate Research Courses
• School of Culture and Communication Postgraduate Research Courses
• School of Engineering and Applied Sciences Postgraduate Research Courses
• School of Health and Social Care Postgraduate Research Courses
• School of Law Postgrad Research Courses
• School of Management Postgraduate Research Courses
• School of Mathematics and Computer Science Postgraduate Research Courses
• School of Psychology Postgraduate Research Courses
• School of Social Sciences Postgraduate Research Courses
• Fees and Funding
• How to Apply For Your Postgraduate Course
• Postgraduate Fees and Funding
• Postgraduate Open Days
• Apply Online
• Postgraduate Careers and Employability
• Accommodation
• Postgraduate Study Video Hub
• Why study at Swansea
• Academi Hywel Teifi
• Student life
• Student Services
• Information for parents and advisors
• Enrolment, Arrivals and Welcome
• Postgraduate Enquiry
• Postgraduate programme changes
• Meet our postgraduate students
• Postgraduate Prospectus
• Fast-track for current students

Are you a UK or International Student?

Top 5 for overall research quality (ref2021), key course details, course overview.

Entry Points: September, January, April, July

Our Population and Health Data Science PhD programme is available on a full-time or part-time basis, over 3 or 6 years. 

The growing pressures on healthcare systems globally are well documented, with chronic diseases, ageing populations and increased incidents of mental health. Advancements in medicine are improving health for more and more people, but inequalities in the healthcare received by people based on where they are born, live and work are prevalent.  Population health aims to address these inequalities, by working to better understand the healthcare needs of groups of people, improving healthcare models and providing innovative solutions to meet people’s health needs. Additionally, healthcare already has an established strong relationship with Information and Communication Technologies (ICT), and is continuously expanding the knowledge forefront as new methods of acquiring data concerning the health of human beings are developed.

Your programme will feature:

• Practice-focused learning
• Supervision team with nominated supervisors
• You will draw on skills from the broader academic community
• Programme seminars and workshops
• Access to Wales’ premier purpose-build medical research facility
• Collaboration with industry and business partners

During your course, you will benefit from our highly regarded specialist facilities. Our vision is to advance medical science through interdisciplinary research and innovation. We are a leading centre for medical research and a unique example of successful collaboration between NHS, academia and industry in the life science and health sector.

We have strong connections with a range of external partners and collaborators, including the NHS;  Swansea Bay University Health Board (SBUHB) ;  Hywel Dda University Health Board ; UK research council; Welsh Government and numerous national and international links. These connections, along with the skills and qualities you develop during your research degree will enhance your CV, and help you stand out in a highly competitive graduate employment market

Entry Requirements

Applicants for PhD must normally hold an undergraduate degree at 2.1 (or Non-UK equivalent as defined by Swansea University). See -  Country-specific Information for European Applicants  and  Country-specific Information for International Applicants . 

English Language

IELTS 6.5 Overall (with no individual component below 5.5) or Swansea University recognised equivalent.  Full details of our English Language policy, including certificate time validity, can be found here .

As well as academic qualifications, Admissions decisions may be based on other factors, including (but not limited to): the standard of the research synopsis/proposal, performance at interview, intensity of competition for limited places, and relevant professional experience.

Reference Requirement

As standard, two references are required before we can progress applications to the College/School research programme Admissions Tutor for consideration.

Applications received without two references attached are placed on hold, pending receipt of the outstanding reference(s). Please note that any protracted delay in receiving the outstanding reference(s) may result in the need to defer your application to a later potential start point/entry month, than what you initially listed as your preferred start option.

You may wish to consider contacting your referee(s) to assist in the process of obtaining the outstanding reference(s) or alternatively, hold submission of application until references are sourced. Please note that it is not the responsibility of the University Admissions Office to obtain missing reference(s) after our initial email is sent to your nominated referee(s), requesting a reference(s) on your behalf.

The reference can take the form of a letter on official headed paper, or via the University’s standard reference form. Click this link to download the university reference form .

Alternatively, referees can email a reference from their employment email account, please note that references received via private email accounts, (i.e. Hotmail, Yahoo, Gmail) cannot be accepted.

References can be submitted to [email protected] .

How you are Supervised

You will be given a supervisory team made up of a primary supervisor and secondary supervisors. This team will provide both academic, and pastoral support whilst you complete your research.

Welsh Provision

Tuition fees.

Tuition fees for years of study after your first year are subject to an increase of 3%.

You can find further information of your fee costs on our tuition fees page .

You may be eligible for funding to help support your study. To find out about scholarships, bursaries and other funding opportunities that are available please visit the University's scholarships and bursaries page .

Current students: You can find further information of your fee costs on our tuition fees page .

Funding and Scholarships

You may be eligible for funding to help support your study.

Government funding is now available for Welsh, English and EU students starting eligible postgraduate research programmes at Swansea University. To find out more, please visit our postgraduate loans page.

To find out about scholarships, bursaries and other funding opportunities that are available please visit the University's scholarships and bursaries page.

Academi Hywel Teifi at Swansea University and the Coleg Cymraeg Cenedlaethol offer a number of generous scholarships and bursaries for students who wish to study through the medium of Welsh or bilingually. For further information about the opportunities available to you, visit the Academi Hywel Teifi Scholarships and Bursaries page.

Additional Costs

Access to your own digital device/the appropriate IT kit will be essential during your time studying at Swansea University. Access to wifi in your accommodation will also be essential to allow you to fully engage with your programme. See our dedicated webpages for further guidance on suitable devices to purchase, and for a full guide on getting your device set up .

You may face additional costs while at university, including (but not limited to):

• Travel to and from campus
• Printing, photocopying, binding, stationery and equipment costs (e.g. USB sticks)
• Purchase of books or texts
• Gowns for graduation ceremonies

How to Apply

Full details of the research degree application process are available  here , and you can  apply online and track your application status here . As part of your application please include a research proposal outlining your proposed topic of study.  Guidance on writing a research proposal is also available .

You can expect to be interviewed following your application to discuss your topic of research and to demonstrate the necessary level of commitment to your studies and training.

It is advisable that you contact us at  [email protected]   before submitting your application. This will ensure we can identify appropriate supervisors, and work with you to refine your proposal.

If you're an international student, find out more at our  international student web pages .

Suggested Application Timings

In order to allow sufficient time for consideration of your application by an academic, for potential offer conditions to be met and travel / relocation, we recommend that applications are made before the dates outlined below. Please note that applications can still be submitted outside of the suggested dates below but there is the potential that your application/potential offer may need to be moved to the next appropriate intake window.

October Enrolment

UK Applicants – 15th August

EU/International applicants – 15th July

January Enrolment

UK applicants – 15th November

EU/International applicants – 15th October

April Enrolment

UK applicants – 15th February

EU/International applicants – 15th January

July Enrolment

UK applicants – 15th May

EU/International applicants – 15th April

EU students - visa and immigration information is available and will be regularly updated on our information for EU students page.

• History, Facts & Figures
• YSM Dean & Deputy Deans
• YSM Administration
• Department Chairs
• YSM Executive Group
• YSM Board of Permanent Officers
• FAC Documents
• Current FAC Members
• Appointments & Promotions Committees
• Ad Hoc Committees and Working Groups
• Chair Searches
• Leadership Searches
• Organization Charts
• Faculty Demographic Data
• Professionalism Reporting Data
• 2022 Diversity Engagement Survey
• State of the School Archive
• Faculty Climate Survey: YSM Results
• Strategic Planning
• Mission Statement & Process
• Beyond Sterling Hall
• COVID-19 Series Workshops
• Previous Workshops
• Departments & Centers
• Find People
• Biomedical Data Science
• Health Equity
• Inflammation
• Neuroscience
• Global Health
• Diabetes and Metabolism
• Policies & Procedures
• Media Relations
• A to Z YSM Lab Websites
• A-Z Faculty List
• A-Z Staff List
• A to Z Abbreviations
• Dept. Diversity Vice Chairs & Champions
• Dean’s Advisory Council on Lesbian, Gay, Bisexual, Transgender, Queer and Intersex Affairs Website
• Minority Organization for Retention and Expansion Website
• Office for Women in Medicine and Science
• Committee on the Status of Women in Medicine Website
• Director of Scientist Diversity and Inclusion
• Diversity Supplements
• Frequently Asked Questions
• Recruitment
• By Department & Program
• News & Events
• Executive Committee
• Aperture: Women in Medicine
• Self-Reflection
• Portraits of Strength
• Mindful: Mental Health Through Art
• Event Photo Galleries
• Additional Support
• MD-PhD Program
• PA Online Program
• Joint MD Programs
• How to Apply
• Advanced Health Sciences Research
• Clinical Informatics & Data Science
• Clinical Investigation
• Medical Education
• Visiting Student Programs
• Special Programs & Student Opportunities
• Residency & Fellowship Programs
• Center for Med Ed
• Organizational Chart
• Leadership & Staff
• Committee Procedural Info (Login Required)
• Faculty Affairs Department Teams
• Recent Appointments & Promotions
• Academic Clinician Track
• Clinician Educator-Scholar Track
• Clinican-Scientist Track
• Investigator Track
• Traditional Track
• Research Ranks
• Instructor/Lecturer
• Social Work Ranks
• Voluntary Ranks
• Adjunct Ranks
• Other Appt Types
• Appointments
• Reappointments
• Transfer of Track
• Term Extensions
• Timeline for A&P Processes
• Interfolio Faculty Search
• Interfolio A&P Processes
• Yale CV Part 1 (CV1)
• Yale CV Part 2 (CV2)
• Samples of Scholarship
• Teaching Evaluations
• Letters of Evaluation
• Dept A&P Narrative
• A&P Voting
• Faculty Affairs Staff Pages
• OAPD Faculty Workshops
• Leadership & Development Seminars
• List of Faculty Mentors
• Incoming Faculty Orientation
• Faculty Onboarding
• Past YSM Award Recipients
• Past PA Award Recipients
• Past YM Award Recipients
• International Award Recipients
• Nominations Calendar
• OAPD Newsletter
• Fostering a Shared Vision of Professionalism
• Academic Integrity
• Addressing Professionalism Concerns
• Consultation Support for Chairs & Section Chiefs
• Policies & Codes of Conduct
• First Fridays
• Fund for Physician-Scientist Mentorship
• Grant Library
• Grant Writing Course
• Mock Study Section
• Research Paper Writing
• Establishing a Thriving Research Program
• Funding Opportunities
• Join Our Voluntary Faculty
• Child Mental Health: Fostering Wellness in Children
• Faculty Resources
• Research by Keyword
• Research by Department
• Research by Global Location
• Translational Research
• Research Cores & Services
• Program for the Promotion of Interdisciplinary Team Science (POINTS)
• CEnR Steering Committee
• Experiential Learning Subcommittee
• Goals & Objectives
• Issues List
• Print Magazine PDFs
• Print Newsletter PDFs
• YSM Events Newsletter
• Social Media
• Patient Care

INFORMATION FOR

• Residents & Fellows
• Researchers

New Department of Biomedical Informatics & Data Science Established at Yale

The Yale Corporation has approved the transition of the Section of Biomedical Informatics & Data Science at Yale School of Medicine (YSM) to the Department of Biomedical Informatics & Data Science (BIDS).

An early leader in biomedical informatics, YSM holds one of the three longest-standing National Institutes of Health (NIH)-supported training programs in this field. Historically, the many YSM faculty engaged in this work were distributed across departments in the school. In 2022, Lucila Ohno-Machado, MD, PhD, MBA, an internationally renowned expert in privacy-enhancing technologies and a National Academy of Medicine member, joined YSM to lead the free-standing BIDS section, coalescing the community and strengthening the infrastructure related to this research, and to serve as deputy dean for biomedical informatics.

Since joining YSM, Ohno-Machado has recruited major leaders in the field to YSM. Today, BIDS includes 12 ladder-track faculty, 13 research-track faculty, and 40 secondary faculty, who have received external awards for leadership and membership from the NIH and professional societies and served on numerous national committees, advisory boards, and university committees.

BIDS has made tremendous progress in carrying out its tripartite mission of research, education, and services, garnering substantial grant funding ($23 million to date). Its members are re-engineering processes for clinical data organization, analyses, and access, as well as developing the computational infrastructure needed to employ artificial intelligence (AI) and advanced analytics in a secure and privacy-protecting manner. Across these efforts, documenting and reducing health disparities is an essential focus.

Attaining department status will enable BIDS to build on this momentum, increasing its national profile and positioning YSM to lead AI in medicine. It further recognizes the achievements of Ohno-Machado and the talented BIDS faculty and strengthens the program’s effort to attract and retain leading talent.

Featured in this article

• Lucila Ohno-Machado, MD, MBA, PhD Waldemar von Zedtwitz Professor of Medicine and Biomedical Informatics and Data Science; Deputy Dean for Biomedical Informatics; Chair, Department of Biomedical Informatics and Data Science

Popular Search Resources for

Health Informatics (MS)

Health Informatics is a cutting-edge discipline and a natural fit to support all health professions. It is a developing discipline with an emphasis on technology as an integral tool to organize, analyze, manage, and use health information, clinical data, images, and knowledge for patient care, health education, administration and research. It is one of the fastest growing fields with a positive job outlook that provides an excellent opportunity to build a career.  

The Master of Science in Health Informatics is a STEM designated program offered by the Health Informatics Program in the School of Health Professions (SOHP). The program consists of a 39-credit curriculum (30-credit core and 9-credit electives) that emphasizes on clinical informatics, human computer interaction, electronic health records, evaluation of healthcare information system, clinical data management, health data analytics and visualization.  

The program is flexible and can be completed on a full-time or part-time basis. The complete MS program is offered in both traditional in-person and distance learning (online) format for student enrollment. In-person classes are offered in the evening, which works well for working professionals who work during the day. The completely online curriculum option is offered in asynchronous format with optional weekly live sessions (evening only) for students to interact with course instructors and other students which are recorded and made accessible to enrolled students.  

The program offers  the opportunity to thrive in a conducive learning environment with a tightly-knitted support system. Rigorous training opportunities are provided and offered to the students to enhance and develop the necessary skills needed to succeed in a health informatics career.  

How to Apply

Program Outcome

Requirements

School of Health Professions

Health Informatics Program

• Phone: (718) 270-7770

Attend an Information Session

Careers & Outcomes

Every day, healthcare organizations collect a universe of data—and they need experts who know how to handle it. There's rising demand for specialists who aren't just technically adept but also understand how medical data is used.

• Systems Administrator
• Health Informaticist
• Clinical Services Manager
• Network Manager
• Clinical Information Specialist
• NYC Health + Hospitals

Meet Our Faculty

Informatics is a young field, but our faculty are seasoned veterans. Learn from experts who specialize in topics such as human-computer interaction, medical decision making, large-scale implementation of electronic medical records, information security, and using technology to reduce health care disparities.

Program Highlights

Put your training to work..

You'll complete a 120-hour internship in one of the city's busiest healthcare environments, such as Downstate and King's County hospital and the NYC Department of Health and Mental Hygiene.

Hands-on help.

When you pitch in at the student-run Brooklyn Free Clinic, which provides free health care services, you'll help the community—and sharpen your own skills.

Build your network.

Meet working professionals and volunteer in the community through the Students of the Medical Informatics Association, a student group.

Take the next step.

• Information Sessions

QUICK LINKS

Degrees and programs powered by experience

Undergraduate

NEWS, DISCOVERY, AND ANALYSIS FROM AROUND THE WORLD

Explore our global campuses

Find unique opportunities for experience-powered learning and discovery.

Our hub for research and graduate education at the intersection of technology, security, and policy

Explore Arlington

Massachusetts

Established in 1898, our first campus is a comprehensive hub for learning, discovery, and urban engagement

Explore Boston

Home to world-class national security and defense research and a magnet for science-based startups

Explore Burlington

North Carolina

An engine for professional education in the life and health sciences

Explore Charlotte

Our hub in Europe, with undergraduate and postgraduate degrees—including a U.S./U.K. double degree—and world-leading network science research

Explore London

Graduate education and entrepreneurship programming to support the rapidly transforming finance and tech economies

Explore Miami

A vibrant center for coastal sustainability research and innovation

Explore Nahant

Our West Coast undergraduate campus offering unique entrepreneurship and social impact programming, and home to the Mills Institute

Explore Oakland

An engine for economic development with graduate degrees and research in technology, and home to the Roux Institute

Explore Portland

Graduate degrees and research focused on the region’s booming tech industry, and undergraduate summer programs

Explore Seattle

Graduate education for high-tech fields in the heart of California’s Big Tech region

Explore Silicon Valley

Preparing professionals to thrive in high-demand fields in North America’s third-largest tech market

Explore Toronto

Professional education aligned with British Columbia’s rising startup and high-tech ecosystem

Explore Vancouver

#LikeAHusky

Plenty of room to do your own thing. Many ways to feel like a Husky.

17 Division I teams, including varsity esports. 55 intramural sports, and 64 club teams. And a packed DogHouse on game nights. Go, Huskies! 

Take Action

Quick Links

Campus Locations

Today, a vanguard of donors is driving Northeastern’s historic $1.3 billion fundraising campaign. With initiatives that span the globe, accelerating outcomes, we’re creating a better world right now. Learn more about our mission

Copyright 2024 Northeastern University