Summary
The Computational Biology and Quantitative Genetics (CBQG) area of study provides students with the rigorous quantitative training and essential skills needed to successfully meet the challenges presented by large-scale public health data — “Big Data” — in biomedical research.
The CBQG area of study is intended as a terminal professional degree that will enable students to launch their careers in bioinformatics. It can also provide the foundation for further doctoral studies in biostatistics, epidemiology, computational biology, and other related fields.
Department overview
The Department of Biostatistics (BIO) and the Department of Epidemiology (EPI) jointly offer the Computational Biology and Quantitative Genetics (CBQG) area of study for the Master of Science (80-credit) degree program.
Degree programs
Student interests
Students who choose the Computational Biology and Quantitative Genetics (CBQG) area of study are interested in a biological background in order to understand and interpret data. CBQG students gain the statistical skills required to appropriately analyze large quantitative datasets, and the epidemiological skills necessary to design, conduct, and analyze experiments.
Career outcomes
The Master of Science (SM-80) CBQG graduates have found employment as bioinformatics analysts or engineers in the following industries:
- Universities
- Hospitals
- Research Organizations
- Pharmaceuticals
- Biotechnology