Summary
Mark Janse is a computational scientist and Research Software Engineer with 14 years of experience building high-performance infrastructure and AI solutions for medical imaging. Currently splitting time between UT Southwestern—where he manages HPC, DevOps and RHEL-based deployments for large-scale AI research—and a PhD at UMC Utrecht focused on deep learning for MRI-based prediction of breast cancer treatment response. He combines production-grade systems skills (massive deployments, security, and 50TB+ imaging repositories) with domain expertise in PyTorch, DICOM, radiomics and C/C++ to turn clinical scans into automated, actionable insights. A seasoned collaborator and reviewer with multiple first-author publications and working-group leadership on metadata standards, he strives to maximize existing data to personalize treatment while minimizing patient and clinic burden. Notably, his background spans hardware prototyping to teaching large cohorts, giving him a rare blend of hands-on engineering, reproducible research, and communication skills.
14 years of coding experience
1 year of employment as a software developer
Gymnasium, Natuur en Techniek & Natuur en Gezondheid, cum laude, Gymnasium, Natuur en Techniek & Natuur en Gezondheid, cum laude at Scheldemond College
Master of Science (M.Sc.), Electrical engineering, cum laude, Master of Science (M.Sc.), Electrical engineering, cum laude at Technische Universiteit Eindhoven
Dutch, English