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: 1
New or Replacement Position: New
Site: Princess Margaret Research Tower
Department: Research
Reports to: Clinician Investigator
Salary Range: $54,902 - $93,333 Per Year
Hours: 37.5 Hours Per Week
Shifts: Day shift
Status: Temporary Full-time
Closing Date: May 20, 2026

Position Summary:
We are seeking a postdoctoral researcher with strong expertise in computational biology, statistical modeling, and analysis of high-dimensional biological and clinical data to contribute to an interdisciplinary research program focused on reproducible computational pipelines for translational cancer research. The lab has a strong focus on developing computational and machine learning approaches for biomarker discovery, therapeutic response modeling, and clinical translation in oncology.

The research program includes several ongoing and evolving projects in glioma and related cancers, broadly focused on tumor microenvironment characterization, liquid biopsy analysis, clinical trial correlative and multi-omics data integration. Current work involves analysis and integration of single-cell sequencing and immune repertoire data, circulating cell-free DNA (cfDNA) for biomarker development and disease classification, metabolomic profiling in relation to clinical variables, and large-scale genomic datasets, including whole-genome sequencing from multi-institutional collaborations. These projects are representative and not exhaustive, and the scope of work may expand to include additional data types and research directions.

Together, these efforts aim to advance translational cancer research through the development and application of computational pipelines and machine learning approaches to characterize disease biology, therapeutic response, and clinical outcomes from high-throughput genomic and clinical data. The successful candidate will work in the Kevin Wang Lab at the Princess Margaret Cancer Centre, and will have the opportunity to contribute to multiple projects and help shape new research directions within the lab.

Duties:

• Design, implement, and maintain reproducible computational pipelines for the analysis and integration of multi-omics and clinical datasets, including single-cell, spatial transcriptomics, cfDNA, and bulk genomic data.
• Develop and apply statistical methods and computational workflows for biomarker discovery, drug response characterization, and tumour microenvironment analysis.
• Perform data curation, harmonization, and quality control across public and institutional datasets, following FAIR data principles.
• Develop and apply machine learning methods alongside statistical approaches to support biomarker discovery and clinical prediction (experience with ML is considered an asset).

Qualifications

• Awarded a PhD within the previous 5 years, or an MD or DDS within the previous 10 years in a relevant quantitative or biomedical discipline, including but not limited to: Computational Biology, Bioinformatics, Systems Biology, or Quantitative Genomics, Biostatistics, Data Science, Biomedical Engineering, or related fields.
• Demonstrated experience developing or applying computational or statistical pipelines to molecular, biological, clinical, or multi-omics data.
• Strong foundation in statistical and computational modeling and data analysis is required; experience with machine learning methods is considered an asset.
• Strong programming skills in Python and/or R, with experience in scientific computing and data analysis libraries (e.g., pandas, NumPy, SciPy, Bioconductor, scikit-learn).
• Experience working with large-scale biomedical datasets, such as multi-omics data, clinical genomics, electronic health record-derived data, or treatment-response datasets.
• Proficiency with reproducible workflow management systems such as Snakemake, Nextflow, or equivalent pipeline frameworks.
• Familiarity with cloud or high-performance computing environments, such as GCP, AWS, SLURM-based clusters, or equivalent infrastructure.
• Understanding of data harmonization, privacy-preserving analysis, secure distributed computing, or clinical data governance is highly desirable.
• Strong publication record, commensurate with career stage, in computational biology, bioinformatics, biostatistics, biomedical data science, or related fields.
• Excellent communication skills and ability to work collaboratively in interdisciplinary teams spanning computational biology, machine learning, software engineering, oncology, and clinical research.

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.