Biomedical Data Science Graduate Program Overview
The Biomedical Data Science Training Program is an interdisciplinary graduate and postdoctoral training program, part of the Department of Biomedical Data Science at Stanford University’s School of Medicine.
Our Educational Mission
DBDS is committed to training the next generation of biomedical data scientists, empowering them to become leaders across academia, industry, government and nonprofit sectors. Our students will learn to ask and answer questions that will advance precision health and medicine and build the foundation for a lifetime of world-class contributions. Our goal is for students to excel in the acquisition, processing and visualization of biomedical data; to develop and implement novel analytical methods to extract knowledge from it; and to master modeling, representation and retrieval of biomedical knowledge. We also require training in understanding ethical, social, economic, and legal issues and consequences of research.
What is Biomedical Data Science?
Biomedical Data Science is a broad term comprising multiple areas.
- Bioinformatics develops novel methods for problems in basic biology.
- Translational Bioinformatics moves developments in our understanding of disease from basic research to clinical care.
- Clinical Informatics develops methods and tools directly applied to patient care.
- Public Health Informatics works on challenging problems from health systems and populations.
- Imaging Informatics addresses intelligent management, interpretation, and annotation of biomedical images.
Take a look at our current courses.
Our Graduate Degrees
The graduate training program offers the PhD degree, and three MS degrees (an academic research-oriented degree, a professional distance-learning masters for part-time students, and co-terminal for Stanford undergraduates). We also have post-doctoral fellows, and offer a distance learning certificate.
- Prerequisites. For a graduate degree, Stanford University requires the applicant to have a bachelor’s degree. We do not require any particular major, but we do require that students have strong undergraduate preparation in computer science/software engineering, mathematics (especially calculus, probability and statistics, and linear algebra), and college-level biology. Applicants with limited backgrounds in these areas should fill the deficiencies prior to applying to our program.
- Curriculum. MS and PhD candidates take coursework in four areas: (1) core DBDS classes, (2) an individual plan with electives in computer science, statistics, mathematics, engineering, and allied informatics-related disciplines, (3) required coursework in social, legal, and ethical issues, (4) unrestricted electives. In addition, PhD candidates are required to choose electives in some area of biology or medicine. Degree candidates also learn important didactic skills by serving as teaching assistants in our core courses.
- Funding. We have been continuously funded by a training grant from the National Library of Medicine since 1984, which provides fellowship support for students who are US citizens and permanent residents. International students bring outside funding or compete for Stanford Graduate Fellowships. Senior graduate students typically receive funding support through their research supervisor.
The History of Our Graduate Program
History at Stanford
The Biomedical Data Science Graduate Program has a long history both at Stanford and internationally, as the first program of its kind. The degree program was initiated in October 1982 as Medical Information Sciences (MIS) and continues to emphasize interdisciplinary education between medicine, computer science, and statistics, offering pre- and postdoctoral degrees and training. The DBDS Program has been supported by a training grant from the National Library of Medicine since 1984, which initially funded only postdoctoral trainees but was broadened to include predoctoral trainees in 1987. The NLM training grant has been renewed every five years since and has provided tuition and stipend support for hundreds of trainees.
Today, the Biomedical Data Science Graduate Program sits in the newly formed Department of Biomedical Data Science and emphasizes methods development and application across the entire spectrum of biology, medicine, and human health.
A Foundation in Medicine and Computer Science
The interaction between Computer Science and other disciplines has produced vibrant areas of research and education at Stanford since the late 1960s; computing activities in the School of Medicine were stimulated even earlier, principally by the Chair of Genetics, Nobel Laureate Joshua Lederberg. Professor Lederberg collaborated with Professor Carl Djerassi (Chemistry) and Professor Edward Feigenbaum (Computer Science) to create what is arguably the first research program that applied the nascent field of artificial intelligence to biomedical problems. Their U.S. Dendral system, which studied the expertise of mass spectroscopists who could interpret an organic compound’s mass spectrum to infer the chemical structure of that compound, is considered the first expert system.
Professor Lederberg’s second key effort was to attract NIH funding for a large medically focused shared computer for the medical school. This computer, known as ACME, was heavily used by Stanford medical researchers, educators, and students until 1973. It brought a computing culture into the environment, which in turn began to attract medical students who had an interest in the intersection of the two fields. Later ACME gave way to the SUMEX-AIM Computer, also funded by NIH with Lederberg as PI. This resource was the first biomedically focused machine on the ARPANet, which evolved to become today’s Internet. The SUMEX Computer was a key resource at Stanford for almost 20 years.
Working closely with Stanley Cohen (a Professor of Medicine who later succeeded Lederberg as Chair of Genetics) and Bruce Buchanan (a research scientist in computer science who was a member of the Dendral Project), Edward Shortliffe undertook a combined MD/PhD with the doctoral degree in a self-designed interdisciplinary program. Further discussion with faculty, students, and researchers emphasized the interest and need to formalize this kind of interdisciplinary education, directly leading to the formation of the MIS graduate program.
The Human Genome Project and a Turn at the Turn of the Century
The launch of the Human Genome Project in 1990 and its completion in 2003 seeded substantial interest and need for computing in the biological community. In 2000 Dr. Russ B. Altman succeeded Dr. Shortliffe as Director of the MIS Program and in recognition of a new mission beyond clinical informatics, to fundamental issues of biomedical knowledge, its representation and its application, the program was renamed Biomedical Data Science Training Program (DBDS). The term Biomedical Data Science represents not only the continued development of medical information systems but also the use of sophisticated computation to study medicine at the molecular, cellular, organismal, and population levels.
Biomedical Data Science Today
On September 1, 2023, the Biomedical Informatics (BMI) training program finalized its last step in merging with the Department of Biomedical Data Science (DBDS) and formally changed its name to the Biomedical Data Science Training Program.
Our trainees admitted after September 1, 2023 will earn their Master’s and PhD degrees in Biomedical Data Science.
The mission of our department and the training program remain fully aligned to “advance precision health by leveraging large, complex, multi-scale real-world data through the development and implementation of novel analytical tools and methods.” Aligning the name of the degree program with department name was widely regarded as both logical and appropriate. More importantly, it reflects a shared vision in our research and education missions that serves to pull our integrated work in biomedical informatics, biostatistics and AI/ML under a unified interdisciplinary umbrella.
The DBDS Training Program at Stanford continues to evolve to meet the needs of biomedical computation and application. Under the guidance of the current Director since 2018 and Chair of the Department of Biomedical Data Science, Professor Sylvia Plevritis, and with support from NLM, the DBDS Program continues to innovate in the areas of Healthcare and Clinical Informatics, Translational Bioinformatics, and Clinical Research Informatics. In addition to historical research thrusts in biomedical knowledge representation and the genetic basis of disease, current research explores algorithms for real world biomedical data, multi-modal data and meta-analysis, medical image analysis, responsible clinical decision making, reproducibility, methods for efficient querying and access to big biomedical data, and more.
Employment in Biomedical Data Science
Prospective students with interest in career directions in Biomedical Data Science should review a list of our Alumni and their current jobs under the People Directory.
Employers
If you have a job posting that you would like to send to the DBDS students and post-docs, please email it to dbds-job-openings at lists.stanford.edu for distribution as we deem appropriate for our audience.
DBDS Current Students and Alumni
The School of Medicine Career Center offers resources for professional and leadership development, resources for the job hunt ranging from presentation skills, resume preparation, interview skills to job hunt strategy. There is a seminar series from both industry and academia, and a number of industry events: demos, job fairs, industry mixers.
The University’s Career Development Center supports undergraduate and graduate career development. They have Career Fairs.
To add your name to the DBDS jobs email list, send your request to the DBDS student services team.
External Job Listings in Biomedical Data Science
AMIA Job Exchange
BayBio’s Job Sites list
BioCareer’s Job site
Bioinformatics.org’s Jobs site
BioinformaticsDirectory listings
Genomeweb’s Job listings
ISCB Jobs Database
Nature’s Jobs list
New Scientist Jobs
NIH’s job listings
Science Career’s
Ziprecruiter
Postdoctoral Positions at Stanford
Please see the descriptions for various opportunities in Biomedical Data Science under Postdoctoral Training
Directions to DBDS Program Offices
Location
The DBDS Program Offices are in the Stanford’s Medical School Office Building (MSOB). The street address is: 1265 Welch Road, Stanford, CA 94305.
MSOB is located on the corner of Campus Drive West and Welch Road, between Panama Street and Welch Road. MSOB is a three story white building with redwood window framing. The exact latitude/longitude is 37.431734, -122.179476. See the map, below.
Parking
There are two options for parking:
- The parking lot in front of our building, which has an entrance on Welch Road. This lot has a few parking spots with coin metered parking.
- The large parking lot across the street on Welch Road. Entrance to the lot is from Stock Farm Road or Oak Road, but you have to drive within the lot towards the corner of Welch Road and Campus Drive. Payment is through cash, coins, or credit card using an automated permit dispenser. Information: https://transportation.stanford.edu/parking
For all questions about the program, email:
Mailing Address: Office Location
Department of Biomedical Data Science Graduate Training Program
Stanford University School of Medicine
1265 Welch Road, MSOB X-343
Stanford, CA 94305-5464