Research Fellow - AI & Data Analytics (AIDA), Radiation Oncology

Responsibilities

The AI and Data Analytics (AIDA) team within the Department of Radiation Oncology is hiring a Research Fellow to help advance the next generation of AI in cancer care (PI: Dr. Andrew Foong). We're seeking an exceptional researcher – technically outstanding, 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 the most trusted name in medicine. The department has access to rich, high-quality cancer treatment data and strong institutional support for innovation. Whether it’s building models to personalize radiation therapy or discovering new insights from multi-modal clinical data, your work will span both foundational research and real-world translation. You'll help bring cutting-edge AI tools into the clinic and shape how technology improves outcomes for cancer patients.

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 will be measured by present-day clinical impact.
• Lead ambitious research: Design and execute novel research projects in collaboration with a multidisciplinary team of computer scientists, physicians, medical physicists, and software engineers.
• Drive growth and visibility: Help shape the direction and culture of AIDA as a new and expanding team. You’ll play a key role in securing internal and external funding through compelling grant proposals and strategic promotion of our work.

• PhD in Computer Science, Biomedical Informatics, Machine Learning, Engineering, Physics, Medical Physics, Applied Math, Statistics, or a related field.
• Strong background in deep learning (e.g., CNNs, transformers) and familiarity with emerging techniques for reasoning and compositionality with large language models.
• Strong Python and ML ecosystem skills (e.g., PyTorch, JAX, scikit-learn, etc.).
• Skilled in writing and passionate about presenting scientific ideas clearly and compellingly.
• Self-motivated, execution-focused, and intellectually independent.

• Stays goal-oriented over method-oriented, and isn’t afraid of unglamorous but high-value work when it matters.

• Comfortable working with real-world, messy, heterogeneous healthcare data.
• A team player who thrives in interdisciplinary environments.

Bonus If You Have

• Prior experience with AI in healthcare settings (clinical data, imaging, EHR).
• Prior experience with radiation oncology.
• Strong software engineering practices (Git, testing, reproducibility).
• Experience writing or contributing to successful grant proposals.
• Demonstrated excellence in research – e.g., strong publication record, impactful projects, open-source contributions.