Postdocs in predictive and explanatory models for the life sciences

We are seeking twelve postdoctoral researchers to join our interdisciplinary data science team, spanning multiple research areas in ecology and evolutionary biology. The postdoctoral researchers will join a collaboration among eight faculty at the University of Wyoming, University of Montana, and University of Nevada-Reno, including Drs. Alex Buerkle, Christopher Weiss-Lehman, Lauren Shoemaker, Sarah Collins, and Daniel Laughlin (UW), Joanna Blaszczak and Matt Forister (UNR), and Bob Hall (UM).

Dramatic increases in the scale and availability of data are profoundly reshaping all domains in the life sciences. Data acquisition and availability from DNA sequencers, environmental sensors, parallel global studies, and imagery are outpacing our capacity for analysis, including the development of models that represent our knowledge of biological processes. Research in our consortium will develop and compete computational, statistical, and machine learning methods for multi-dimensional data to create predictive and explanatory models for the life sciences. The project focuses on three research areas: (1) connecting genome to phenome (particularly in the context of evolutionary biology), (2) mechanistic modeling of species interactions and community diversity, and (3) time series of material and energy flux in aquatic ecosystems.