Biomedical and Health Informatics, PhD
Phone: 216.368.3725
Kim Krajcovic - Education Program Manager
informatics@case.edu
Degree: Doctor of Philosophy (PhD)
Field of Study: Biomedical and Health Informatics
Program Overview
The PhD BHI program enables informaticians from a variety of backgrounds, including practicing clinicians, computer scientists, biostatisticians, basic science researchers, and data scientists, to acquire essential skills to improve human health. The PhD program features three themes that allows informaticians to build on their existing strengths with advanced expertise in:
- Data Analytics using statistical methodologies
- Biomedical research
- Computing and Data Science
This program is a full-time, research-oriented program that educates students to advance research in biomedical informatics for careers in industry, academia, health care, and government. The Population and Quantitative Health Sciences (PQHS) department has a rich history of providing an outstanding interdisciplinary learning environment that enables students to apply informatics methods to advance basic science and clinic research using advanced computing methodologies with a particular focus on dynamic Artificial Intelligence research. This unique environment leverages world-class resources available at the four affiliated hospital systems in Cleveland: Cleveland Clinic Foundation, University Hospitals Cleveland Medical Center, MetroHealth systems, and the Veteran Affairs of Cleveland.
All first-year full-time students in the PhD program are fully funded by the School of Medicine (Stipend, Tuition, and Health Insurance are included). After the conclusion of their first year, students will be supported by grants (research and training) held by their research mentor.
Important Note: The program information contained on this page is current as of April 1, 2026. For the most current information, we advise you to review the PhD in Biomedical and Health Informatics program handbook. You can find the most recent Program Handbook here.
PhD Policies
For PhD policies and procedures, please review the School of Graduate Studies section of the General Bulletin.
Program Requirements
Core Curriculum
All incoming PhD students take a required curriculum supplemented by additional coursework as determined by their mentoring or dissertation committees. The required curriculum contains courses that expose students to each of the required domains.
| Code | Title | Credit Hours |
|---|---|---|
| Required Courses: | 12 | |
| Introduction to Data Structures and Algorithms in Python | ||
| AI in Medicine: Knowledge Representation and Deep Learning | ||
| Statistical Methods I | ||
| Statistical Methods II | ||
| Biomedical and Health Domain Courses | 3 | |
| Epidemiology: Introduction to Theory and Methods | ||
| Computation and System Design Domain Courses | 3 | |
| Choose one of the following: | ||
| Analysis of Algorithms | ||
| Database Systems | ||
| Introduction to Bioinformatics | ||
| Advanced Algorithms | ||
| Software Engineering | ||
| Machine Learning & Data Mining | ||
| Geospatial Analytics for Biomedical Health Applications | ||
| Data Analytics Domain Courses | 3 | |
| Choose one of the following: | ||
| Applied Probability and Stochastic Processes for Biology | ||
| Categorical Data Analysis | ||
| Longitudinal Data Analysis | ||
PQHS 467 | ||
| Secondary Analysis of Large Health Care Databases | ||
| An Introduction to GIS for Health and Social Sciences | ||
| Required Research Courses: | 2 | |
| On Being a Professional Scientist: The Responsible Conduct of Research | ||
| Responsible Conduct of Research for Advanced Trainees a | ||
| Communicating in Population Health Science Research | ||
| Research Ethics in Population Health Sciences | ||
| Research Seminar b | ||
| Electives c | 13 | |
| Dissertation d | 18 | |
| Dissertation Ph.D. | ||
| Total Credit Hours | 54 | |
- a
The SOM requires that PhD students who are 4 years beyond their initial RCR training in IBMS 500, register for IBMS 501.
- b
Must take for at least six semesters.
- c
Electives are chosen in consultation with the student’s mentor and mentoring committee.
- d
PhD students can take between 1-9 credit hours of PQHS 701 per semester.
Sample Plan of Study
| First Year | ||
|---|---|---|
| Fall | Credit Hours | |
| PQHS 413 | Introduction to Data Structures and Algorithms in Python | 3 |
| PQHS 431 | Statistical Methods I | 3 |
| PQHS 501 | Research Seminar | 0 |
| Domain Area Course or Elective | 3 | |
| Credit Hours | 9 | |
| Spring | ||
| PQHS 416 | AI in Medicine: Knowledge Representation and Deep Learning | 3 |
| PQHS 432 | Statistical Methods II | 3 |
| PQHS 501 | Research Seminar | 0 |
| Domain Area Course or Elective | 3 | |
| Credit Hours | 9 | |
| Second Year | ||
| Fall | ||
| PQHS 444 | Communicating in Population Health Science Research | 1 |
| PQHS 501 | Research Seminar | 0 |
| Domain Area Course or Elective | 3 | |
| Domain Area Course or Elective | 3 | |
| Domain Area Course or Elective | 3 | |
| Credit Hours | 10 | |
| Spring | ||
| IBMS 500 | On Being a Professional Scientist: The Responsible Conduct of Research | 1 |
| PQHS 501 | Research Seminar | 0 |
| Domain Area Course or Elective | 3 | |
| Domain Area Course or Elective | 3 | |
| Domain Area Course or Elective | 3 | |
| PQHS 445 | Research Ethics in Population Health Sciences | 0 |
| Credit Hours | 10 | |
| Third Year | ||
| Fall | ||
| PQHS 501 | Research Seminar | 0 |
| PQHS 701 | Dissertation Ph.D. | 3 |
| Elective | 1 | |
| Credit Hours | 4 | |
| Spring | ||
| PQHS 501 | Research Seminar | 0 |
| PQHS 701 | Dissertation Ph.D. | 3 |
| Credit Hours | 3 | |
| Fourth Year | ||
| Fall | ||
| PQHS 501 | Research Seminar | 0 |
| PQHS 701 | Dissertation Ph.D. | 6 |
| Credit Hours | 6 | |
| Spring | ||
| PQHS 501 | Research Seminar | 0 |
| PQHS 701 | Dissertation Ph.D. | 3 |
| Credit Hours | 3 | |
| Total Credit Hours | 54 | |