Markham, On Postdoctoral fellow in ai for medical Jobs – 1 Openings This Week

Post-Doctoral Fellow (SRI) - Physical Sciences - Temporary Full-time 2026-16669
Sunnybrook Health Sciences Centre —Toronto, ON
- Temporary
- Doctoral degree
- Computer Science
- Engineering
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Post-Doctoral Fellow (SRI) - Physical Sciences - Temporary Full-time 2026-16669
Sunnybrook Health Sciences Centre —Toronto, ON
The Holland Bone and Joint Program at Sunnybrook Research Institute is seeking a Postdoctoral Fellow to contribute to projects focused on medical image analysis…
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Post-Doctoral Fellow (SRI) - Physical Sciences - Temporary Full-time 2026-16669

Sunnybrook Health Sciences Centre -
Toronto, ON

Quick apply

Job details

Temporary | Full-time

Qualifications

TensorFlow
Law
Doctoral degree
Computer Science
PyTorch
Engineering
Databases
Docker
Natural language processing
Python

Full job description

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

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Post-Doctoral Fellow (SRI) - Physical Sciences - Temporary Full-time 2026-16669

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