With 80, 60, and 42.5-credit programs available to students with differing career goals and levels of prior training, the MSc in Biostatistics provides training in statistical theory in the interest areas of Biostatistics and Bioinformatics, along with a variety of statistical, computational, and bioinformatics methods for application in medicine and public health.
The MSc in Health Data Science provides students with the rigorous quantitative training and essential computing skills needed to manage and analyze health science data to address important questions in public health, medicine, and basic biology.
Students can also apply to this new MSc program in Computational Biology and Quantitative Genetics, offered jointly offered with the Department of Biostatistics and the Department of Epidemiology.
The PhD program is designed to prepare students for careers in the theory and practice of biostatistics and bioinformatics, and includes training in the development of methodology, consulting, teaching, and collaboration on a broad spectrum of problems related to human health, genomics, and basic biology.
Students with an area of interest in bioinformatics or computational biology must select a minimum of 4 of the following 7 courses:
- Introduction to Data Structures and Algorithms
- Advanced Regression in Statistical Learning
- Probability Theory and Applications II
- Statistical Inference II
- Analysis of Multivariate and Longitudinal Data
- Bayesian Methods in Biostatistics
- Introduction to Computational Biology and Bioinformatics (required)
- Advanced Computational Biology and Bioinformatics
- Advanced Population and Medical Genetics