Postdoctoral Researcher - AI for Computational Pathology

2w2 weeks ago

University Health Network

Toronto, CA · Temporary · C$54,902 – C$93,333

About this role

UHN is Canada’s #1 hospital and world’s #1 publicly funded hospital, with major research in oncology and genomic medicine. We seek a highly motivated Postdoctoral Fellow for the Computational Pathology program, developing advanced AI algorithms for cancer diagnosis and prognosis. This role offers work at the intersection of machine learning, digital pathology, and clinical translation.

The position contributes to cutting-edge multimodal AI research in one of Canada’s most data-rich environments. Daily work involves building AI/ML models using digital pathology data and integrating imaging, clinical, and molecular data. Collaboration with clinicians ensures solutions impact real-world clinical workflows.

Join TeamUHN at Toronto General Hospital’s Laboratory Medicine Department, reporting to the Medical Director. Work in a multidisciplinary team within UHN’s largest hospital-based research program, affiliated with the University of Toronto. Engage with national and international discovery, education, and patient care.

Advance UHN’s vision to build A Healthier World through innovative research. Publish in leading journals, contribute to grants, and mentor trainees. This temporary full-time role provides direct clinical impact in a collaborative setting.

Requirements

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

Responsibilities

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

Benefits

Work alongside talented and inspiring healthcare professionals
Join Canada’s top research hospital with largest hospital-based research program
Contribute to national and international source for discovery, education and patient care