Summary
Daan Geijs is a Solution Delivery Lead and machine learning engineer with nine years of experience at the intersection of biomedical imaging, computational pathology, and healthcare software delivery. Trained in Biomedical Engineering (University of Twente) with an MSc in Science Education, he transitioned from teaching physics to a PhD project implementing deep learning into pathology workflows for skin cancer, then moved into deploying AI in hospitals as a forward-deployed engineer. He builds production-ready systems (Django/Wagtail, AWS, Terraform) and has led development of health-focused platforms while freelancing on software engineering projects. Known for marrying rigorous academic research—tumor segmentation and IHC image analysis—with pragmatic deployment, he now focuses on agentic AI and scalable clinical integrations. Based in Nijmegen, he combines hands-on model work with delivery leadership, making complex AI tools usable for frontline clinicians.
9 years of coding experience
1 year of employment as a software developer
Master’s Degree Science Education and Communication, Master’s Degree Science Education and Communication at University of Twente
High School Voorbereidend Wetenschappelijk Onderwijs, High School Voorbereidend Wetenschappelijk Onderwijs at St.- Ludger College
Natuurkunde en Wiskunde B, Natuurkunde en Wiskunde B at Boswell-Beta
English, German, Dutch