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Research Fellow - AI & Data Analytics (AIDA), Radiation Oncology
Research Fellow - AI & Data Analytics (AIDA), Radiation OncologyMayo Clinic • Rochester, NY, United States
Research Fellow - AI & Data Analytics (AIDA), Radiation Oncology

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

Mayo Clinic • Rochester, NY, United States
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Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans – to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic.

Benefits Highlights

  • Medical : Multiple plan options.
  • Dental : Delta Dental or reimbursement account for flexible coverage.
  • Vision : Affordable plan with national network.
  • Pre-Tax Savings : HSA and FSAs for eligible expenses.
  • Retirement : Competitive retirement package to secure your future.

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). Were 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. Youll 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.
  • Qualifications

  • 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.
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