Biomedical & Health Informatics PhD Curriculum

The core curriculum of the doctoral program consists of four required courses:

  • Data Structures and Algorithms (PQHS 413)
  • Artificial Intelligence in Medicine: Knowledge Representation and Deep Learning (PQHS 416)
  • Statistics Methods I (PQHS 431)
  • Statistics Methods II (PQHS 432)

Students also select three elective courses from the three concentration areas for a total of seven core courses (21 credit hours).

Further, students work with their research committee to identify and enroll in four additional courses in a concentration of their choice.

Additionally, students are required to enroll in Research Seminar (PQHS 501), Research Ethics (IBMS 500) and Research Communications (PQHS 444).

Research Rotations

In addition to coursework in the first year, all students will do three research rotations with potential mentors. The purpose of a rotation is to provide students with exposure to the laboratory/scientific culture pervasive in that discipline and research group, and to determine if the student-mentor fit is appropriate. The rotation gives the student and faculty member an opportunity to determine if they have similar work styles, and if the scientific culture and training will result in successful training for the student. By the end of the first year, all students will choose a mentor and a lab in which to do their dissertation work.

Seminars and Required Research Activities

Exposure to contemporary research is facilitated by department-wide seminars that include talks by leading experts both from off- and on-campus. As part of their training, all students participate in these seminars, including as speakers. This fosters the development of communication skills expected of successful researchers. As noted above, students are required to enroll in research ethics (IBMS 500) and research communications (PQHS 444).

PhD students in the BHI program will follow the same guidelines for dissertation proposals as outlined for other PQHS department PhD programs. For more information, contact the program director.

Summary of the curriculum requirements for the doctoral program

Required core courses (4 courses, 12 credits)

  • Data Structures and Algorithms (PQHS 413)
  • Artificial Intelligence in Medicine: Knowledge Representation and Deep Learning (PQHS 416)
  • Statistical Methods I (PQHS 431)
  • Statistical Methods II (PQHS 432)

Required distribution of elective courses (3 courses, 9 credits)

Choose one course from each core concentration:

  • Biomedical and Health Informatics
  • Computation and System Design
  • Data Analytics

Elective courses (4 courses, 12 credits)

Choose four additional electives from cores noted above or from among 14 other approved electives

  • The selection of elective courses is made by the student in consultation with mentoring/advising committee

Required research activities (3 credits)

  • Research Seminar: PQHS 501 (0 credits - must take for at least 6 semesters)
  • Research Ethics: IBMS 500 (1 credit)
  • Communicating in Population Health Science Research: PQHS 444 (2 x 1 credit)

Required dissertation (18 credits)

  • Required to pass written/oral qualifying exam prior to dissertation credits