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Overview
Students in the medical school track will complete the standard curriculum for the PhD in Data Science program. In addition, students in this track will be able to take elective courses offered at the NYU School of Medicine and to collaborate with faculty there. Medical school track students will start the program with at least one faculty mentor in CDS (selected from the PhD Advisory Group) and at least one mentor in the Medical School (see list of application domains and relevant faculty below).
The elective curriculum will be customized in consultation with the student’s mentors to best align with their research interests.
Possible electives are listed below:
- Bioinformatics (BMSC-GA 2604)
- Introduction to Healthcare AI (BMSC-GA 4455)
- Methods in Quantitative Biology (BMSC-GA 4449)
- Advanced Integrative Omics (BMSC-GA 4498)
- Deep Learning in Medicine (BMSC-GA 4493)
- Applied Sequencing Informatics (BMSC-GA 4452)
- Proteomic Informatics (BMSC-GA 4437)
- Clinical Decision Support (BMSC-GA 4483)
- Evaluation Methods for Predictive Risk Models (BMSC-GA 4499)
- Fundamentals of MRI (BMSC-GA 4404)
- Practical MRI 1 (BMSC-GA 4427)
- Practical MRI 2 (BMSC-GA 4428)
- Medical Imaging (BMSC-GA 4426)
Moreover, rotations will be offered with faculty at the School of Medicine.