Two-year fellowship developing future leaders in applying AI/ML to pediatric oncology. Fellows learn to prioritize clinical questions, develop and deploy models, and implement solutions in care delivery—working with large datasets, statistics, quality improvement, and implementation science. Academic year runs July 1 – June 30.
Eligibility Criteria:
-
Open to fellows across disciplines (e.g., oncology, surgery, pathology, diagnostic imaging) pursuing cancer AI/ML research.
-
Clinical fellows who have completed (or will have completed by start) core clinical training.
-
Prior coding experience is an asset; willingness to learn coding and take AI/ML courses during fellowship is required.
-
Must source two supervisors: (1) Clinical Supervisor (your practice area); (2) Technical Supervisor with AI/ML expertise (may be external to SickKids if a proven leader).
-
Up to 20% clinical time during the fellowship.
-
Introductory AI/ML courses required and encouraged within first 3 months (e.g., Introduction to Machine Learning, AI in Healthcare Specialization).
-
A project/model is not required at the start.
Funding Details:
-
Stipend: $98,566/year + modified benefits (two years).
-
Supervisor contribution: $22,000 toward salary (offset if external funding is obtained).
-
Resources: Laptop provided; up to $500 for AI/ML courses (year 1).
-
Structure & oversight: Formal Fellowship Oversight Committee (FOC) (supervisors + AI/ML mentors + lab collaborators) meets bimonthly (Y1) and quarterly (Y2). Progress reports twice per year; coding skills assessed at end of Y1.
Deadline:
-
Start: July 1, 2026.
-
Submission deadline: October 17, 2025.
-
Notifications: By end of November (if accepted).
Where to Go for Further Information:
-
Inquiries: [email protected].