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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI & Data Analytics Research Fellow-Radiation Oncology - **Company:** Mayo Clinic - **Location:** Rochester, MN, United States - **Salary:** $71,992.0 - $84,221.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Health Informatics, Clinical Data Repository, Decision Support Systems, Python (Programming Language), Machine Learning, Pytorch, Deep Learning, Scikit Learn, Information Technology, Data Analytics - **Published:** June 19, 2026 - **Apply:** https://jobs.mayoclinic.org/job/rochester/ai-and-data-analytics-research-fellow-radiation-oncology/33647/93729609296 ## About the Role * 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. ## Description Why Mayo Clinic 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 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. Qualifications * 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. Exemption Status Exempt Compensation Detail $71,992.20- $84,220.50 / year; Education, experience and tenure may be considered along with internal equity when job offers are extended. Benefits Eligible Yes Schedule Full Time Hours/Pay Period 80 Schedule Details Monday - Friday Weekend Schedule as needed International Assignment No Site Description Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is. Equal Opportunity All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the 'EOE is the Law'. Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization. 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