Research Associate - Health Care Delivery
About the role
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. 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.
Responsibilities
- We seek a highly motivated Research Associate with strong foundations in both theoretical artificial intelligence/machine learning (AI/ML) and applied data-driven research, particularly in health and biomedical domains. The position is for a 1–2-year paid fellowship working under the mentorship of Dr. Hojjat Salehinejad. The ideal candidate will demonstrate deep expertise in the mathematical and algorithmic principles underlying modern AI systems, as well as the ability to translate these methods into impactful real-world solutions to improve patient outcomes.
- Designing and developing novel AI/ML algorithms grounded in solid theoretical principles
- Translating advanced computational methods into deployable solutions for healthcare systems
- Leading interdisciplinary collaborations
- Publishing high-impact scientific work
- Contributing to health services research (HSR), health policy, and quantitative health sciences
- Research activities may intersect with different clinical departments across the Mayo Clinic where advanced computational and statistical modeling approaches are required
- The successful candidate will combine strong