Summary
Nicholas Vence is a data scientist with 18 years of interdisciplinary experience applying statistical modeling, machine learning, and HPC to problems spanning dietary epidemiology, stem-cell classification, and quantum laser-atom simulations. He combines hands-on coding in R, Python, C/C++ and Arduino with UNIX-based HPC workflows, having run simulations on Jaguar and built distributed PDE solvers and MADNESS-based quantum codes. His work bridges research and applied engineering—calibrating proton CT detectors, automating robotic beamlines, and improving SVM classification accuracy from 85% to 90%—and he communicates technical results through teaching and peer-reviewed publications. Based in Berrien Springs, MI, he has taught at multiple universities and contributed data products to the 96,000-participant Adventist Health Study 2, demonstrating an unusual blend of experimental lab control, large-cohort analytics, and public-facing storytelling.
18 years of coding experience
10 years of employment as a software developer
PhD, Atomic and molecular physics, PhD, Atomic and molecular physics at University of Tennessee-Knoxville
BS/BA, Physics/Math, BS/BA, Physics/Math at Southern Adventist University
English, Spanish, Sign Language