CMS Group Alumni
Jerome Nilmeier is now a data engineering fellow at Insight Data Science in San Francisco.
Jerome Nilmeier is currently a postdoctoral researcher in the Computational Materials Science Group. His original appointment was in the Biosciences and Biotechnology division, where he developed and implemented a variety of techniques for automatically detecting the function of a protein based on given sequence. This included structure prediction and refinement, as well as docking and molecular dynamics studies. From this work, an automated in-house catalytic site identification procedure was developed using a combination of graph theoretic search techniques and machine learning approaches.
He has developed and implemented variety of Monte Carlo techniques, primarily in the context of biochemical simulation. The original approaches included a combination of exact and approximate methods designed to address specific issues arising in sampling of proteins, which include loop closure algorithms, rotamer sampling methods, as well as surface generalized Born models of protein solvation. From this work, exact Monte Carlo approaches which have broader applicability and that rely on nonequilibrium theorems were developed, which can be used not only to develop efficient simulation procedures, but also to analyze nonequilibrium data. He is currently developing parallelization techniques for kinetic Monte Carlo algorithms with applications to lattice dynamics in materials.