Summary
Nicholas Charron is a Senior Machine Learning Scientist with a PhD in computational physics and nine years of experience applying deep learning to problems in physics, chemistry, and protein biophysics. He builds, scales, and validates neural-network-based models and coarse-grained force fields, translating research-grade methods into robust, open-source software for HPC environments. At institutions from Rice University and CERN to Zuse Institute Berlin and now Genentech, he has combined hands-on model development with HPC consulting and cluster resource management to enable scientific AI at scale. His work blends theoretical rigor (Koopman-inspired dynamics, transferability studies) with practical engineering—mentoring students, maintaining research software, and guiding production deployments. Based in Houston, he is passionate about making advanced scientific ML accessible and reproducible, often focusing on physicochemical interpretability rather than black-box performance.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Physics and Astronomy, Doctor of Philosophy (Ph.D.), Physics and Astronomy at Rice University
BA, Physics, BA, Physics at Boston University
English, French