Summary
Susan Dorsher is a computational physicist and software developer with over 15 years of experience building numerical simulations, algorithms, and data analysis pipelines for gravitational-wave searches, black hole dynamics, cosmology, and exoplanet statistics. She is fluent in Python, C++, FORTRAN, MATLAB and C, has ported large scientific codes with 1e-11 agreement, and implements mathematically rigorous, statistically correct solutions that tie theory, experiment, and data together. Her work spans hands-on HPC-style projects (ray-traced black hole visualizations, Monte Carlo Newtonian-noise models) to prototype search algorithms for LIGO, and she recently refreshed her skillset with a Machine Learning and Deep Learning certificate. Based in Minnesota and working remotely, she seeks part-time roles that respect disability accommodations and leverage her strengths as an implementer and cross-disciplinary problem solver. Colleagues describe her as direct, independent-minded, and precise—someone who prefers leading by technical example rather than management. An underrated asset: she routinely converts advanced analytic formalisms into robust, reproducible code that other teams can validate and extend.
11 years of coding experience