We have a postdoctoral opening in computational/mathematical biology. Our group focuses on problems at the interface of mechanistic modeling and machine learning, leveraging the strengths of each approach. Our present interests are in scalable persistent homology applied to biological datasets, mechanistic single-cell data modeling using the Hamilton-Jacobi equation, correlating phylogenetic inference of contact maps for proteins with machine-learning predictions, and the deduction of quantum-mechanical coarse-grained Hamiltonians for large biomolecules from molecular dynamics simulations. Excellent computational and/or mathematical skills and the willingness and ability to learn new techniques are essential. The NIH is strongly committed to a diverse biomedical workforce.
