- Compensation: CAD 54,902 - CAD 82,352 - yearly

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.

Union: Non-Union
Number of Vacancies: 1
Current or Replacement Position: New
Site: MaRS
Department: Research
Reports to: Senior Scientist
Salary Range: $54,902 - $82,352 annually
Hours: 37.5 Hours Per Week
Shifts: Monday - Friday; Day Shifts
Status: Temporary Full-time (2-Year Contract)
Closing Date: November 26, 2026

Position Summary

We seek a postdoctoral fellow with strong expertise in computational biology, bioinformatics, biomedical data science, and/or AI/ML to join a major interdisciplinary initiative focused on developing computational approaches for translational cancer research.





The ideal candidate will have a strong quantitative or computational background together with demonstrated experience in AI applied to genomic, transcriptomic, multi-omics, molecular, pharmacological, or clinical data. The position is particularly suited to candidates interested in addressing biologically and clinically meaningful questions at the intersection of computational oncology, cancer genomics, machine learning, biomarker discovery, and scientific AI.

A major focus of the position will be computational biomarker discovery and therapeutic response modeling across cancer types and treatment modalities. This will include identifying predictive and response-associated molecular signatures, characterizing disease- and treatment-related biological mechanisms, prioritizing potential therapeutic targets, and developing computational models of drug and treatment response. Methodological priorities will include multimodal and representation learning, as well as foundation-model approaches that integrate multiple biological and clinical data layers to improve prediction, generalization, and biological interpretation.

A second major focus will be the development of scalable, reproducible, and privacy-aware computational frameworks for multi-cohort translational studies. This will include agentic AI-enabled approaches for data harmonization, annotation, quality control, integration, analysis, and scientific interpretation across public and institutional datasets,



as well as distributed and federated approaches in settings where sensitive data remain under local governance.

Together, these efforts aim to advance computational oncology, biomarker development, therapeutic discovery, and precision medicine by combining modern machine learning with rigorous computational biology, multimodal biomedical data integration, and reproducible distributed analysis.

The candidate will be working in the Haibe-Kains Lab at the Princess Margaret Cancer Centre , University Health Network , within a multi-institutional research collaboration involving the Rosalind & Morris Goodman Cancer Institute at McGill University, as well as other academic, clinical, and industry partners.

What We Offer

A highly collaborative, interdisciplinary research environment spanning computational biology, oncology, clinical informatics, and AI

Access to large-scale proprietary clinical datasets (tumour biopsies, treatment outcomes, longitudinal genomics) alongside major public resources

State-of-the-art GPU cluster and cloud computing infrastructure with dedicated allocations

Mentorship from senior faculty with strong track records in Nature/Science-family publications and competitive grant funding

Opportunities to collaborate with clinical teams, pharmaceutical industry partners, and international research consortia

Support for conference travel, professional development, and independent fellowship applications

Duties

Design and implement multimodal computational and foundation models integrating molecular, genomic, transcriptomic, multi-omics, treatment, and clinical data.

Develop transfer learning strategies to therapeutic prediction tasks, inclu

📌 Postdoctoral Researcher (Toronto)
🏢 University Health Network
📍 Toronto