biomedical informatics phd

Biomedical Informatics

• Academics & Education

PhD in Biomedical Informatics

• PhD Course Requirements
• PhD Mentors
• Current Students

Our PhD program provides intensive research training and coursework in biomedical informatics. The primary goal of the program is to train the next generation of students to be independent scientists who can transform data into knowledge to improve the health of individuals and populations.

CURRICULUM CUBE

The strengths of our program faculty are utilized in the building of the curriculum. This figure shows the expertise by application area (green, yellow, orange, red), methodology (grey), and focal research area (teal). After a year of core courses, students join an application track and choose methods courses as needed. The research foci are woven through the curriculum and demonstrate departmental strengths, although students are not limited to these fields.

Application Tracks

The strengths of our program faculty are utilized in the building of our curriculum and broken down into 4 application areas: , translational bioinformatics, public health informatics, clinical research informatics, clinical informatics, methods tracks, there are 4 methods tracks, and students select courses from one or more track to meet their learning needs:, data science, ai, analytics & computational methods, ethical issues in informatics & data science, sociotechnical design & evaluation, standards & interoperability, research threads, there are 4 focus research threads that have been designed to allow the trainee to find their starting point and build their skill set and knowledge:, precision medicine, health disparities & diversity, disease prevention, the phd degree requires approximately 40 hours of formal classwork with a grade of b or better. a phd student must pass a written and oral comprehensive exam after the first year of study. graduate work at this or other institutions, including courses taken for an ms degree, may be applied to the phd coursework requirement at the discretion of the student's advisory committee. after completion of coursework, the student must pass a phd written and oral qualifying examination. in addition to the classwork, 14 or more hours of research work (taken as bmi 7970) are required. this work must lead to completing and defending an original phd dissertation demonstrating the student's capabilities to conceive and execute an independent research project., the admission process is rigorous, and we attempt to provide funding for all admitted candidates. we work to match people's interest with research projects mentors. funding includes:, annual $40,000 stipend, 100% tuition coverage, health insurance, support for research conferences, more information, first department of biomedical informatics, established in 1964, internationally recognized as a leader in biomedical informatics, available support via the national library of medicine training grant and other resources, abundant research opportunities with leaders in the field, phd application deadlines, december 1st.

Online Application

Frequently Asked Questions

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 .​

Clinical Informatics Education at Stanford

Clinical Informatics Fellowship

MS & PhD in Biomedical Informatics

MS in Clinical Informatics Management

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Program Contacts

MS & PhD in Biomedical Informatics

Program focus.

Biomedical informatics is an interdisciplinary field that combines ideas from computer science and quantitative disciplines (statistics, data science, decision science) to solving challenging problems in biology and medicine. The BMI program provides coursework and mentored research training, with a focus on methods development, drawing heavily on quantitative and computational approaches.

Program Benefits

The BMI program offers the MS and PhD degrees. The MS degrees can be completed on-campus or through the distance education program while employed full-time.

Student Profile

Students in the program typically spend 2-5 years in coursework and research, depending on the degree. Some enter the program with prior graduate (MS, PhD, or MD) training.

Program Contact Information

Biomedical Informatics Program

Email:  [email protected]

Visit the Biomedical Informatics Website 

Division of Biology & Biomedical Sciences

• Biomedical Informatics & Data Science

The Biomedical Informatics and Data Science (BIDS) PhD program will provide opportunities for graduate students with diverse backgrounds to gain expertise in the field of biomedical informatics and data science, to train as future biomedical researchers and industry leaders in biomedical informatics and data science core competencies, and to engage in scholarly activities under the guidance of experienced informatics faculty. Beyond an educational program, the mission of BIDS is to support biomedical informatics and data science practice through applied research in real-world settings.

The objectives of the BIDS program are to: 

• Expand students’ knowledge in data science theories and applications in biomedical informatics;
• Provide training and hands-on research and industry experience in biomedical informatics and data science;
• Assist students in enhancing and applying their skills in translational science, real-world problem solving, and dissemination of knowledge;
• Encourage students to pursue careers in academia and/or industry through exposure to professional role models or mentors; and
• Develop and improve students’ skills in interdisciplinary teamwork and communication. 

The BIDS program spans the fields of Data Science and Biomedical Informatics, which we define as follows:

• Biomedical Data Science  is the study of the generalizable extraction of knowledge from biomedical data; and
• Biomedical Informatics  is the science of information applied to or studied in the context of biomedicine. 

(Payne PR, Bernstam EV, Starren JB. Biomedical informatics meets data science: current state and future directions for interaction. Jamia Open. 2018 Oct;1(2):136-41.)

Throughout their training, learners will interact with patients, providers, and the healthcare data ecosystem in addition to working at the bench. The BIDS program promotes collaboration and partnerships in solving problems in clinical practice, individual and population health, and biomedical research, through the optimal use of information. Due to its interdisciplinary nature, the BIDS program offers learners great flexibility when creating individual education plans based on interests, experience, and future goals. 

Core research tracks and subfields  

Biostatistics and data science.

The goal of the Biostatistics and Data Science track is to train independent and innovative researchers who will contribute to the development and application of cutting-edge statistical and data science methodologies in health science disciplines. The track provides a balance of theory, methods, and applications of biostatistics and data science that are central to modern interdisciplinary research. Under the supervision of advisors, PhD students participate in the design of clinical studies and are involved in the analysis, inference, and interpretation of these studies. 

Biomedical Informatics

Through the Biomedical Informatics track, students will have training and research opportunities in the five subdisciplines of biomedical informatics, as defined by the American Medical Informatics Association (AMIA) :

• Applied Clinical Informatics (ACI)   focuses on supporting and elevating clinical informatics practice through research translation, which is essential to fill the gaps between practice and research. ACI involves the application of innovative measurement and informatics approaches to inform and improve clinical practice.
• Consumer Health Informatics (CHI)   involves views from consumers or patients and focuses on information structures and processes to empower individual’s management of their own health. CHI investigates consumers’ needs and integrates consumers’ preferences into health information systems.
• Clinical Research Informatics (CRI) involves the use of informatics in the discovery and management of new knowledge relating to health and disease. Specifically, CRI manages information related to clinical trials as well as secondary use of clinical data.
• Translational Bioinformatics (TBI)  is the development of storage, analytic, and interpretive methods to optimize the transformation of increasingly voluminous biomedical data into proactive, predictive, preventative, and participatory health.
• Population Health Informatics (PopHI) integrates aspects of public health, clinical informatics, and health care delivery with the target of improving health care system effectiveness and the well-being of communities and populations.

There is a wide range of research interests between faculty affiliated with the BIDS program, some of which include:

• Human genetic analysis
• Telemedicine & mobile health
• Cognitive computing & machine learning
• Systems biology
• Epidemiology & public health
• Neuroimaging
• Computational mass spectrometry & proteomics
• Survival Analysis
• Clinical decision support & workflow

Students in the BIDS program will typically take six (6) to seven (7) courses during their first year. Students will also participate in three laboratory rotations over the fall and spring semesters of Year 1 prior to selecting a thesis lab. Students are expected to complete the following coursework during their entire graduate education:

DBBS required courses

Graduate Research Fundamentals Ethics and Research Science – typically taken in Year 2

Program required courses

Introduction to Biomedical Informatics I Introduction to Biomedical Informatics II Introduction to Biomedical Data Science I Introduction to Biomedical Data Science II

Three (3) semesters of advanced electives

Four (4) semesters of bids journal club and seminar series, qualifying exam.

In the spring and/or summer semesters of Year 2, students must pass a Qualifying Exam (QE). Following a successful QE defense, students will identify and finalize their committee and complete their thesis proposal by December 31st of Year 3.

Thesis committee, proposal, and defense

In the summer and/or fall semesters of Year 2 after rotations are completed, students will select a thesis advisor and begin working in their thesis labs. Students will then select a thesis committee and complete their thesis proposal. Students will complete their thesis research, defense, and graduation over the rest of their graduate career. Most students graduate within five (5) to six (6) years of beginning their program.

Graduate Program Administrator:  Kayla Bryant ​

Faculty Director:  Philip Payne, PhD, FACMI Adam Wilcox, PhD

• Biochemistry, Biophysics, & Structural Biology
• Cancer Biology
• Computational & Systems Biology
• Developmental, Regenerative, & Stem Cell Biology
• Ecology & Evolutionary Biology
• Molecular Cell Biology
• Molecular Genetics & Genomics
• Molecular Microbiology & Microbial Pathogenesis
• Neurosciences
• Plant & Microbial Biosciences

Health Sciences Informatics, PhD

School of medicine.

The Ph.D. in Health Sciences Informatics offers the opportunity to participate in ground-breaking research projects in clinical informatics and data science at one of the world’s finest biomedical research institutions. In keeping with the traditions of the Johns Hopkins University and the Johns Hopkins Hospital, the Ph.D. program seeks excellence and commitment in its students to further the prevention and management of disease through the continued exploration and development of health informatics, health IT, and data science. Resources include a highly collaborative clinical faculty committed to research at the patient, provider, and system levels. The admissions process will be highly selective and finely calibrated to complement the expertise of faculty mentors.    

Areas of research:

• Clinical Decision Support
• Global Health Informatics
• Health Information Exchange (HIE)
• Human Computer Interaction
• Multi-Center Real World Data
• Patient Quality & Safety
• Population Health Analytics
• Precision Medicine Analytics
• Standard Terminologies
• Telemedicine
• Translational Bioinformatics

Individuals wishing to prepare themselves for careers as independent researchers in health sciences informatics, with applications experience in informatics across the entire health/healthcare life cycle, should apply for admission to the doctoral program.

Admission Criteria

Applicants with the following types of degrees and qualifications will be considered:

• BA or BS, with relevant technical and quantitative competencies and a record of scientific accomplishment as an undergraduate; 
• BA or BS, with relevant technical and quantitative competencies and a minimum of five years professional experience in a relevant field (e.g., biomedical research, data science, public health, etc.); or
• MA, MS, MPH, MLIS, MD, PhD, or other terminal degree, with relevant technical and quantitative competencies

Relevant fields include: medicine, dentistry, veterinary science, nursing, ancillary clinical sciences, public health, librarianship, biomedical science, bioengineering and pharmaceutical sciences, and computer and information science. An undergraduate minor or major in information or computer science is highly desirable.

The application is made available online through Johns Hopkins School of Medicine's website . Please note that paper applications are no longer accepted. The supporting documents listed below must be received by the SOM admissions office by December 15 of the following year. Applications will not be reviewed until they are complete and we have all supporting letters and documentation.

• Curriculum Vitae (including list of peer-reviewed publications and scientific presentations)
• Three Letters of Recommendation
• Statement of Purpose
• Official Transcripts from undergraduate and any graduate studies
• Certification of terminal degree
• You are also encouraged to submit a portfolio of published research, writing samples, and/or samples of website or system development

Please track submission of supporting documentation through the SLATE admissions portal.

If you have questions about your qualifications for this program, please contact [email protected]

Program Requirements

The PhD curriculum will be highly customized based on the student's background and needs. Specific courses and milestones will be developed in partnership with the student's advisor and the PhD Program Director.

The proposed curriculum is founded on four high-level principles:

• Achieving a balance between theory and research, and between breadth and depth of knowledge
• Creating a curriculum around student needs, background, and goals
• Teaching and research excellence
• Modeling professional behavior locally and nationally.

Individualized curriculum plans will be developed to build proficiencies in the following areas:

• Foundations of biomedical informatics: e.g., lifecycle of information systems, decision support
• Information and computer science: e.g., software engineering, programming languages, design and analysis of algorithms, data structures.
• Research methodology: research design, epidemiology, and systems evaluation; mathematics for computer science (discrete mathematics, probability theory), mathematical statistics, applied statistics, mathematics for statistics (linear algebra, sampling theory, statistical inference theory, probability); ethnographic methods.
• Implementation sciences: methods from the social sciences (e.g., organizational behavior and management, evaluation, ethics, health policy, communication, cognitive learning sciences, psychology, and sociological knowledge and methods), health economics, evidence-based practice, safety, quality.
• Specific informatics domains: clinical informatics, public health informatics, analytics
• Practical experience: experience in informatics research, experience with health information technology.

Basic Requirements & Credit Distribution

• 15 "core" quarter credits (5 courses)
• 8 quarter credits of Student Seminar & Grand Rounds
• 60 elective quarter credits
• 6 quarter credits practicum/research rotation
• 36 mentored research quarter credits (12 in year 1, 24 in year 2)
• Research Ethics