SM Computational Biology and Quantitative Genetics at Harvard University

This program provides students with the statistical and epidemiological skills needed to manage and analyze large-scale genomic datasets that are increasingly common in biomedical, biological, and public health research areas. The Master of Science in Computational Biology and Quantitative Genetics is designed to provide you with the statistical skills required to appropriately analyze large quantitative datasets as well as the epidemiological skills necessary to design, conduct, and evaluate experiments. You will receive training in quantitative methods, including linear and logistic regression, survival analysis, longitudinal data analysis, statistical computing, clinical trials, statistical consultation and collaboration, and epidemiology.

Faculty: Harvard T.H. Chan School of Public Health  |  Duration: On Campus (Fall start) • Full-time (2 years)  |  Study mode: full-time  |  Location: Cambridge, MA, United States

What you will study

Required courses include BST 220: Applied Regression Methods; BST 280: Introductory Genomics & Bioinformatics for Health Research; EPI 201: Introduction to Epidemiology Methods I; EPI 249: Molecular Biology for Epidemiologists; BST 227 Introduction to Statistical Genetics.

Career pathways

The Master of Science (SM-80) CBQG graduates have found employment as bioinformatics analysts or engineers in the following industries: Minimum prerequisite for entrance: Bachelor’s degree or non-U.S. equivalent An undergraduate degree (major or minor concentration) in mathematical sciences or allied fields (statistics, pure or applied mathematics, data science, computer science, bioinformatics, economics, etc.) with a strong interest in the biological sciences.

Official programme page