Date Posted:
4/6/2026
Location:
Toronto, ON, Canada
Reference No.:
2026-16669
Position Type:
Temporary full-time
Department:
FTE Status:
1.00
Hours of Work:
8 hrs
Campus Site:
Bayview
Shifts Weekday Required:
Days
Shifts Weekend Required:
No Weekends
Statutory Holiday(s) Required:
No
Vacancy Status:
New
Contract End Date:
3/16/2026
One of Canada's Top 10 Research Hospitals, Sunnybrook Research Institute is developing innovations in care for the more than 1.3 million patients the hospital cares for annually.
Sunnybrook Research Institute is the research enterprise of Sunnybrook Health Sciences Centre, a teaching hospital fully affiliated with the University of Toronto. Research spans three Toronto-based campuses, eight programs and three scientific platforms. Our main aims are to understand and prevent disease, and to develop treatments that enhance and extend life. Our vision is to invent the future of health care. Each year, we conduct about $100 million in research across 500,000 square feet, including in the world’s first Centre for Research in Image-Guided Therapeutics.
Position Overview
The Holland Bone and Joint Program at Sunnybrook Research Institute is seeking a Postdoctoral Fellow to contribute to projects focused on medical image analysis, advanced visualization, and analysis of electronic health record (EHR) data within a federated network.
The successful candidate will conduct research at the intersection of:
• Deep learning for medical image analysis
• Image-based biomarker development
• Multimodal modeling combining imaging and longitudinal EHR data
• Federated learning infrastructure
• Large language models (LLMs) for automated EHR labeling
• Advanced visualization and surgical simulation
This role offers the opportunity to work on clinically translational AI research in spine, trauma, and oncology applications within a secure, multi-institutional data framework.
Key Responsibilities
• Develop and validate deep learning algorithms for medical image segmentation, registration, and quantitative biomarker extraction (CT, MRI)
• Design multimodal predictive models integrating imaging biomarkers with longitudinal clinical data
• Contribute to federated learning workflows for multi-site model training and validation
• Develop and evaluate LLM-based pipelines for structured data extraction from EHR text
• Support development of VR-enabled visualization and patient-specific simulation tools
• Conduct cross-site validation and generalization studies
• Publish peer-reviewed manuscripts and present at scientific conferences
• Mentor graduate students and trainees
Qualifications:
Required:
• PhD received in last 5yrs in Biomedical Engineering, Computer Science, Medical Physics, Data Science, or related discipline
• Strong background in deep learning (PyTorch or TensorFlow)
• Experience in medical image analysis
• Strong programming skills (Python required)
• Demonstrated research productivity and publication record
Preferred:
• Experience working with clinical or OMOP-CDM databases
• Experience with federated learning frameworks
• Experience applying NLP or LLMs to clinical text
• Familiarity with Docker/containerized pipelines
• Interest in translational and clinically deployed AI systems