Summary
Josh Bevan is a Senior Scientific Programmer Analyst with 12 years of experience applying computer science, applied math, and mechanical engineering to high-performance computing and numerical simulation. Based in Boston, he optimizes and parallelizes scientific codes for the MGHPCC cluster, supporting workflows that consume hundreds of millions of core hours and petabytes of data. He brings hands-on expertise in Python, C++, Fortran, MATLAB, OpenMP/MPI, and numerical PDEs, and has delivered domain-specific solutions from kinetic Monte Carlo and Fast Multipole adaptations to custom algebraic solvers and image post-processing pipelines. Josh pairs rigorous mathematical training—PhD work on high-order numerical methods and proofs of convergence—with practical project leadership, automation, and regulatory-aware engineering from industry roles. He’s actively expanding into machine learning, NLP, and quantum computing, translating classical HPC techniques to emerging computational paradigms. A practical problem-solver, he’s as comfortable proving numerical stability on paper as he is squeezing performance out of heterogeneous CPU/GPU clusters.
12 years of coding experience
8 years of employment as a software developer
UMass Lowell
University of Illinois Urbana-Champaign
French