Postdoctoral Researcher

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).