Computational Epidemiology and Systems Modeling

专业介绍

The Master of Science (MS) program in Computational Epidemiology and Systems Modeling trains students to become highly skilled epidemiologists who apply mathematical and statistical models to understand and analyze public health problems. Students are rigorously trained on how to manage and analyze big data relevant to a wide range of data science applications. They will learn to develop and apply dynamic models to important problems in the epidemiology of both infectious and non-communicable disease to optimize intervention strategies. Using their newly acquired skills, students will leverage the wealth of big data including remote sensing imagery, the microbiome, medical and surveillance records, genomics and metagenomics. 

Epidemiological models and simulation-based analyses are increasingly used to inform public health policy and practice. The curriculum aims to provide students with the knowledge, skills, and hands-on experience necessary to become epidemiologists who are proficient in mathematical modeling, computational science, and the statistical tools that connect these models to real-world data and problems. Graduates of the program will be well-prepared for careers in research, academia, data management, industry, and health informatics. 

The degree is awarded by the University of Michigan’s Rackham Graduate School through the Department of Epidemiology in the University of Michigan School of Public Health.