AI & I Data Analytics Research Fellow – Radiation Oncology

The AI and Data Analytics (AIDA) team within the Department of Radiation Oncology at Mayo Clinic is hiring a Research Fellow to help advance the next generation of AI in cancer care: https://radonc-aida.github.io ). We’re looking for an exceptional researcher that is technically strong, intellectually curious, and motivated by real-world impact. You’ll join a uniquely positioned institution. Mayo Clinic treats over 1.4 million patients annually and is consistently ranked among the most trusted names in medicine. Within this environment, AIDA operates as a fast-moving, high-impact team building and deploying AI tools directly into clinical workflows. Over the past year, our tools have moved beyond prototypes into active clinical use, supporting hundreds of clinicians across multiple specialties. Several have been recognized at institutional and national forums, reflecting both their technical innovation and measurable impact on care delivery. This is a rare opportunity to work on AI systems that are not only published, but used, evaluated, and iterated on in real clinical environments. Whether it’s building models to personalize cancer treatment, extracting insights from longitudinal clinical data, or deploying tools that streamline physician workflows, your work will span both foundational research and real-world translation. We are looking for someone who could thrive in top-tier tech companies or academia but chooses to work here because you want your work to matter to patients, to clinicians, and to the future of healthcare. What You’ll Do Deploy impactful AI : Develop, implement, and evaluate machine learning models in real clinical settings. Success is measured not just by publications, but by adoption, usability, and clinical impact. Work on end-to-end systems : Contribute to AI tools that integrate into clinical workflows ranging from predictive modeling to automation of documentation and decision support. Lead ambitious research : Design and execute novel research projects in collaboration with a multidisciplinary team of physicians, physicists, data scientists, and engineers. Translate research into practice : Help move ideas from concept to prototype to deployment to real-world use, learning what actually works in healthcare. PhD in Computer Science, Machine Learning, Biomedical Informatics, Engineering, Physics, Applied Math, Statistics, or a related field. Strong background in modern machine learning (e.g., deep learning, transformers, or related methods). Strong experience with Python and ML ecosystems (e.g., PyTorch, JAX, scikit-learn). Strong communication skills: able to write and present complex ideas clearly. Self-motivated, execution-focused, and comfortable owning ambiguous problems.