Postdoctoral Researcher

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

Position Summary:
We are seeking a highly motivated postdoctoral fellow to join our research team to lead projects using artificial intelligence (AI) in radiology. The successful candidate will support and lead image-based projects focused on developing and validating machine learning and deep learning approaches for quantitative image analysis (e.g., radiomics). Responsibilities include mentoring graduate students, contributing to manuscript writing and editing, and maintaining and enhancing image processing pipelines for high-throughput analysis of clinical imaging data.

The selected candidate will play a key role in driving interdisciplinary collaborations within the University Health Network (UHN) and with external partners. Additional duties include assisting in grant preparation, contributing to project design and analysis, and supporting hypothesis-generating studies across a range of clinical domains. Candidates should have a strong background in medical imaging, data science, or a related field, with demonstrated experience in computational research and scientific writing.

The candidate will be working in the Haibe-Kains Lab at the Princess Margaret Cancer Centre, University Health Network.

Duties:

Hands-on experience in high performance computing and image analysis in Python in a cluster environment (Slurm). An understanding of cancer image data curation and standardization would be helpful.

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.