-
projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
-
projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
-
Purdue’s strategic focus on health equity and population health. Program Goals and Learning Objectives The fellow will gain experience in: Designing and conducting pharmacoepidemiologic studies in cancer and
-
and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
-
using R for statistical analysis and in statistical modeling. Sound working knowledge of unix shell, high performance compute clusters and git. Willingness to learn and use a scripting language (e.g
-
modeling. Contribute to and drive forward the project’s work plan and study goals. Ideal Candidates: The ideal candidate will hold a Ph.D. in Biology, Biochemistry, Epidemiology, Genetics, Genomics
-
the culture of the College of Liberal Arts (#ThinkBroadlyLeadBoldly). Pay band: In addition to annual salary of up to $75,000, this position provides office space, computer equipment, and $2500 in yearly