Summary
Maximilian Konrad is a PhD student and applied physicist focused on explainable and adaptive AI for MR-guided online adaptive radiotherapy, combining clinical deployment with methodological work on outlier detection, interpretability, and automated QA. He bridges research and production: building AI inference services for organ-at-risk and target delineation while previously developing full-stack systems (Django REST APIs, AWS, Angular) that taught him to prioritize usable design for clinicians. With a background in biophysics and a master’s thesis on ML for cervical cancer radiotherapy planning, he brings deep domain knowledge in medical imaging, X-AI, and Bayesian statistics. Ten years of experience across research, healthcare, and industry give him a pragmatic mindset for turning sophisticated models into robust, clinician-friendly tools.
10 years of coding experience
5 years of employment as a software developer
Master's degree, Physics, Master's degree, Physics at Syddansk Universitet - University of Southern Denmark
Bachelor of Science - BS, Physics, Bachelor of Science - BS, Physics at University of Augsburg
English, Danish, German