Eugene, Oregon, United States
Computational physicist specializing in molecular dynamics simulation—both building high-performance pipelines and developing enhanced sampling methods. 5+ years architecting CUDA-accelerated engines, HPC/GPU workflows, and reproducible scientific software for drug discovery. Proficient in Python/C++ for numerical methods and production-grade API development. Experienced integrating quantum chemistry tools with MD engines and translating complex simulations into actionable results for cross-functional teams. Open to simulation engineering, scientific software, and computational infrastructure roles.
Designed and operated high-throughput molecular dynamics pipelines using OpenMM and AMBER24, applying enhanced sampling strategies metadynamics, accelerated MD, MCMC, and restraint-driven approaches to resolve protein structures by integrating HDX-MS experimental data with computational modeling. Delivered structural characterization across protein-ligand, protein-protein, and molecular glue complexes directly informing compound prioritization, SAR, and informed optimization across 4+ campaigns spanning FBDD, small molecule, large molecule, and molecular glue modalities. Partnered with medicinal chemists to characterize binding pocket dynamics, electrostatics, and hydrophobic features guiding compound design toward nanomolar affinities. Performed protein-protein and protein-ligand docking with HADDOCK and leveraged AlphaFold2 and Boltz2 for structure prediction within integrative workflows. Architected and implemented a high-performance mass spectrometry signal processing engine in C++ with Python bindings, enabling rapid HDX-MS data extraction beyond the capabilities of existing tools. Developed HPC analysis APIs, validation frameworks, and compute benchmarks to ensure correctness and performance across releases.
Simulation and analysis of non-equilibrium classical materials towards mapping onto non-hermitian quantum mechanical system