Postdoctoral Researcher

Responsibilities

• Design, implement, and maintain reproducible computational pipelines for the analysis of multi-omics and clinical datasets
• Develop and apply statistical methods and computational workflows for biomarker discovery and tumor microenvironment analysis
• Perform data curation, harmonization, and quality control across public and institutional datasets following FAIR principles
• Apply machine learning methods alongside statistical approaches to support clinical prediction and drug response characterization

Requirements

• PhD in a quantitative or biomedical discipline (e.g., Computational Biology, Bioinformatics, Data Science, or related fields) awarded within the last 5 years
• Demonstrated experience developing computational or statistical pipelines for molecular, biological, or multi-omics data
• Strong programming proficiency in Python and/or R, including scientific computing libraries
• Experience working with large-scale biomedical datasets, such as single-cell sequencing or clinical genomics
• Proficiency with workflow management systems like Snakemake or Nextflow
• Familiarity with cloud or high-performance computing environments (e.g., GCP, AWS, or SLURM)

Preferred Qualifications

• Experience with machine learning methods for biomarker discovery
• Knowledge of data harmonization, privacy-preserving analysis, or clinical data governance
• Strong publication record in computational biology or related fields

Benefits

• Competitive compensation packages
• Membership in the Healthcare of Ontario Pension Plan (HOOPP)
• Flexible work environment
• Opportunities for professional development and promotion
• Access to corporate discounts including travel, restaurants, and fitness

About the Company

University Health Network (UHN) is Canada’s #1 hospital and a global leader in publicly funded healthcare and research. As a research hospital affiliated with the University of Toronto, UHN operates multiple sites, including the Princess Margaret Cancer Centre, driving discovery in oncology, neurosciences, and genomic medicine.