Company Description

UHN is Canada’s #1 hospital and the world’s #1 publicly funded hospital. With 10 sites and more than 44,000 TeamUHN members, UHN consists of Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre, Toronto Rehabilitation Institute, The Michener Institute of Education and West Park Healthcare Centre. As Canada's top research hospital, the scope of biomedical research and complexity of cases at UHN have made it a national and international source for discovery, education and patient care. UHN has the largest hospital-based research program in Canada, with major research in neurosciences, cardiology, transplantation, oncology, surgical innovation, infectious diseases, genomic medicine and rehabilitation medicine. UHN is a research hospital affiliated with the University of Toronto.

UHN’s vision is to build A Healthier World and it’s only because of the talented and dedicated people who work here that we are continually bringing that vision closer to reality.

www.uhn.ca

Job Description

Union: Non-Union
Number of vacancies: 2
New or Replacement Position: New
Site: Toronto General Hospital
Department: Laboratory Medicine
Reports to: Medical Director
Salary Range: $54,902 to $93,333 per annum
Hours: 37.5 hours per week
Shifts: Days
Status: Temporary Full-Time
Closing Date: May 8, 2026

Position Summary
We are seeking a highly motivated Postdoctoral Fellow to join our Computational Pathology (CPath) program, focusing on the development of advanced AI algorithms for cancer diagnosis and prognosis.
This is a unique opportunity to work at the intersection of machine learning, digital pathology, and clinical translation within one of the most data-rich and collaborative environments in Canada. The successful candidate will contribute to cutting-edge, multimodal AI research while directly impacting real-world clinical workflows.
Duties

• Develop and evaluate novel AI/ML models for cancer detection, grading, and prognosis using digital pathology data.
• Design and implement multimodal learning frameworks integrating imaging, clinical, and molecular data.
• Collaborate with clinicians and researchers to define clinically meaningful problems and solutions.
• Publish research findings in leading machine learning and medical journals/conferences.
• Contribute to grant writing and research project development.
• Mentor graduate students and research trainees as appropriate.

Qualifications

• PhD in Computer Science, Biomedical Engineering, Electrical Engineering, or a related field.
• Strong background in machine learning and deep learning (e.g., PyTorch, TensorFlow).
• Experience with medical imaging or computer vision.
• Proven track record of publications in relevant venues.
• Strong programming skills (e.g., Python).
• Ability to work independently and collaboratively in a multidisciplinary environment.
• Experience in digital pathology or whole slide image analysis preferred
• Familiarity with multimodal learning approaches preferred
• Experience with large-scale data processing and high-performance computing preferred
• Knowledge of clinical workflows and healthcare data preferred

Additional Information

Why join UHN?

In addition to working alongside some of the most talented and inspiring healthcare professionals in the world, UHN offers a wide range of benefits, programs and perks. It is the comprehensiveness of these offerings that makes it a differentiating factor, allowing you to find value where it matters most to you, now and throughout your career at UHN.

• Competitive offer packages
• Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP https://hoopp.com/)
• Close access to Transit and UHN shuttle service
• A flexible work environment
• Opportunities for development and promotions within a large organization
• Additional perks (multiple corporate discounts including: travel, restaurants, parking, phone plans, auto insurance discounts, on-site gyms, etc.)

Current UHN employees must have successfully completed their probationary period, have a good employee record along with satisfactory attendance in accordance with UHN's attendance management program, to be eligible for consideration.

All applications must be submitted before the posting close date.

UHN uses email to communicate with selected candidates. Please ensure you check your email regularly.

Please be advised that a Criminal Record Check may be required of the successful candidate. Should it be determined that any information provided by a candidate be misleading, inaccurate or incorrect, UHN reserves the right to discontinue with the consideration of their application.

UHN is an equal opportunity employer committed to an inclusive recruitment process and workplace. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their requirements known.

We thank all applicants for their interest, however, only those selected for further consideration will be contacted.