-
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
-
management. Requisite skills include DNA extractions (ideally from noninvasive sources), PCR, sequencing and basic statistical modeling (e.g., simple regression). Desired skills include qPCR, ddPCR, and/or
-
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
-
effort on active research projects and publish and present research results. Research work will focus on Computation Fluid Dynamics (CFD) models involving multiphase reacting flow simulations with emphasis
-
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