Research Fellow PC - Radiation Oncology - Waddle lab

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.

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-enabled clinical research and cancer care: (Use the "Apply for this Job" box below)..

We are looking for an exceptional researcher who is intellectually curious, clinically engaged, technically capable, and motivated by real‑world impact. Candidates with experience in LLM pipelines, digital pathology, computational pathology, multimodal AI, or the integration of pathology, imaging, and clinical data are especially encouraged to apply.

You will 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 developing, evaluating, and translating AI tools into clinical and research workflows.

Our work sits at the intersection of clinical oncology, biomedical data science, digital pathology, medical imaging, and applied AI. Over the past year, several of our tools have moved beyond prototypes into active clinical use, supporting clinicians across multiple specialties. These tools have been recognized at institutional and national forums for their innovation, usability, 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.

The Research Fellow will contribute to projects focused on understanding and extracting value from complex clinical data, including electronic health records, longitudinal oncology data, clinical notes, pathology reports, digitized pathology images, imaging‑derived data, treatment information, and patient outcomes. A major emphasis of the role will be using AI, including large language models and multimodal learning methods, to support clinical data retrieval, cohort discovery, data abstraction, documentation workflows, decision support, biomarker discovery, and translational cancer research.

Whether it is identifying clinically meaningful patterns in cancer treatment data, using LLMs to retrieve and summarize relevant patient information, analyzing digital pathology or imaging data, building tools that support physician workflows, or designing studies that evaluate AI in real‑world care settings, your work will span both rigorous research and practical clinical translation.

We are looking for someone who wants to work closely with physicians, physicists, pathologists, data scientists, engineers, and clinical teams to develop AI tools that matter to patients, clinicians, and the future of healthcare.

• Advance clinically meaningful AI research
  :
  Design and execute research projects that use AI and data analytics to address important questions in radiation oncology, cancer care, digital pathology, and clinical operations.
• Work with real-world clinical data
  :
  Analyze and interpret complex clinical datasets, including structured EHR data, clinical notes, pathology reports, digitized pathology images, treatment records, outcomes data, and longitudinal patient information.
• Use LLMs for clinical data retrieval and abstraction
  :
  Apply large language models and related methods to retrieve, summarize, structure, and validate information from clinical records, pathology reports, and other healthcare data sources.
• Contribute to multimodal clinical AI
  :
  Help develop methods that integrate multiple data types, such as clinical text, structured EHR data, pathology data, imaging data, treatment data, and outcomes.
• Support digital pathology and image‑based research
  :
  Contribute to AI‑enabled analysis of pathology-related data, including whole‑slide images, pathology reports, tumor characteristics, biomarkers, and clinicopathologic correlations.
• Translat…