An ongoing project in the Laboratory for Systems Medicine uses methods from topology to model complex healthcare data. One goal is to test the ability of topological methods to improve our understanding of predictive outcome models. Another is to develop interactive tools to more efficiently explore patient populations. The work involves software development, data analysis, and predictive modeling.
Students will learn about all phases of the project and contribute in areas that best match their skills and interests. No advanced mathematical or biomedical training is required, but quantitative, analytic, and scientific thinking are essential, and familiarity with study design, statistics, discrete mathematics, or R programming would be advantageous. Students will meet regularly with the mentor and an MD–PhD student collaborator to coordinate training, development, analysis, and writing.