BMDS-PHD - Biomedical Data Science (PhD)
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Program Overview
The Biomedical Data Science Program is interdisciplinary and offers instruction and research opportunities leading to MS and PhD degrees in Biomedical Data Science. The program emphasizes research to develop novel computational methods that can advance biomedicine. Students receive training in investigating new approaches to conceptual modeling and developing new algorithms that address challenging problems in the biological sciences and clinical medicine.
Admissions Information
The program can provide flexibility and complement Stanford’s other applied medical research opportunities. Special arrangements may be made for those with unusual needs or those simultaneously enrolled in other degree programs within the university. Similarly, students with prior relevant training may have the curriculum adjusted to eliminate requirements met as part of prior training.
The GRE is not required for admission.
Individuals wishing to prepare themselves for careers as independent researchers in biomedical data science, with applications experience in bioinformatics, clinical informatics, or imaging informatics, should apply for admission to the doctoral program. Graduate Degrees summarizes the university’s basic requirements (residence, dissertation, examination, and so on) for a doctorate.
Minimum Units in the Program
Minimum University Units
The PhD program requires 135 units; 52 of those units should be formal coursework (classroom-based courses, not research units).
A cumulative GPA of 3.0 or greater to remain in good academic standing.
In the first year, at least two research rotations are required.
Doctoral students generally advance to PhD candidacy after passing the qualifying exam, which takes place by the end of the second year of training. A student’s academic advisor is primarily responsible for the program’s adequacy, which the Biomedical Data Science Executive Committee regularly reviews. The student must fulfill these requirements and apply for admission to candidacy for the PhD by the beginning of the third year.
During the third year of training, each doctoral student must give a thesis pre-proposal seminar that describes evolving research plans.
Students are expected to participate regularly in course Biomedical Data Science Student Seminar and a research colloquium. Regardless of their enrollment, they should attend all meetings throughout their graduate training and a research colloquium appropriate to their interests.
Students are expected to complete the core offerings in biomedical data science. These courses should be taken for a grade.
To achieve in-depth mastery, PhD students are expected to create a program of study with graduate-level courses in computer science, statistics, and other technical informatics-related disciplines. The program of study may focus on aspects of these disciplines, including machine learning, statistical modeling, artificial intelligence, data mining, image analysis, human-computer interaction, and data visualization.
In addition to the 10-13 units students will earn through the Required Courses listed above, students should also choose courses from the electives list below to reach the total of 24 units needed for this requirement.
Crosslisted offerings for any of the courses listed above are accepted in place of the offering listed.
No more than nine units in courses numbered 100-199, and the rest should be 200 or above
course Programming Methodology and course Programming Abstractions cannot be counted for this requirement
All courses should be formal classroom-based courses, not research units
Up to eight units of this portion of the core curriculum may be taken on a Satisfactory/No Credit basis
Students are expected to be familiar with issues regarding responsible conduct of research, reproducibility of research, and ethical, legal, social, organizational, and behavioral aspects of the impact of biomedical informatics technologies on society. Courses that fulfill this requirement can be found by entering “dbds::ethics” in the Explore Courses search box. PhD students should take course. The Responsible Conduct of Research in their first year. These courses may be taken on a Satisfactory/No credit basis.
Students should take classes relevant to their application area interests. The core curriculum and domain biology/medicine requirements should be completed by the end of the second year of graduate study.
Domain Biology courses can be taken as Credit/No Credit (CR/NR).
Students may fulfill this requirement with any Stanford graduate courses, including courses taken to satisfy program prerequisites. Up to six units of unrestricted electives can be taken Pass/Fail.
Each student must be a teaching assistant for two courses as assigned by the Biomedical Data Science Executive Committee; one should be completed in the first two years of study. Students may register for up to three BMDS 295 Biomedical Informatics Teaching Methods units to obtain credit for each teaching assistantship.
After applying for Terminal Graduate Registration (TGR) status and completing 135 units, the PhD candidate should register each quarter for BIOMEDIN 802 TGR PhD Dissertation so that their research effort may be counted toward the degree.
Each student must present and defend their dissertation work before a University Oral Examination Committee that includes at least one member of the DBDS Faculty. The committee determines whether the student’s general knowledge of the field and the details of their completed research are sufficient to be granted the doctoral degree. Further information about the Oral Examination and the submission of the written dissertation is in the DBDS Student Handbook and university policies cited therein.
The student is expected to demonstrate an ability to present scholarly material and research in a lecture at a formal seminar.
The most important requirement for the PhD degree is the dissertation. Each student must secure the agreement of a member of the DBDS faculty to act as the doctoral dissertation advisor or obtain departmental approval for a dissertation advisor to be appointed from outside the major department. This approval will depend on research rationale, potential advisor’s commitment to program’s rules, and identification of a DBDS faculty to participate in the thesis committee. See DBDS Student Handbook for details.
After applying for Terminal Graduate Registration (TGR) status and completing 135 units, the PhD candidate should register each quarter for BMDS 802 TGR PhD Dissertation so that their research effort may be counted toward the degree.
Each student must present and defend their dissertation work before a University Oral Examination Committee that includes at least one member of the DBDS faculty. The committee determines whether the student’s general knowledge of the field and the details of their completed research are sufficient to be granted the doctoral degree. Further information about the Oral Examination and the submission of the written dissertation is in the DBDS Student Handbook and university policies cited therein.
The student is expected to demonstrate an ability to present scholarly material and research in a lecture at a formal seminar.
The student is expected to demonstrate an ability to present scholarly material in concise written form. Each student must write a paper suitable for publication, usually discussing their doctoral research project. The student’s advisor must approve this paper as suitable for submission to a refereed journal before the department confers the doctoral degree.
The dissertation must be accepted by a doctoral dissertation reading committee composed of the principal dissertation advisor and two other readers. A fourth reader may be added at the discretion of the student and the principal advisor.