Postdoctoral Researcher

Responsibilities

• Work with cutting-edge data from single-cell transcriptomics, epigenomics, and spatial multiomics
• Develop novel computational methods to identify cellular populations using multiomic integration
• Track cancer-cell evolution across treatments using deep-learning architectures
• Identify biomarkers associated with different anti-cancer treatments
• Determine tumor microenvironmental factors associated with disease progression and treatment resistance
• Disseminate research through high-impact publications and international conferences
• Develop reproducible pipelines for high-throughput data analysis
• Contribute to grant applications to support ongoing research

Requirements

• PhD in Computer Science, Mathematics, Bioinformatics, Computational Biology, or a related field awarded within the last 5 years
• Proven track record of published method development
• Strong proficiency in Linux and Python
• Strong background in statistics, machine learning, and/or deep learning
• Experience with version control using Git and GitHub
• Excellent written and verbal communication skills
• Ability to work both independently and within a collaborative team environment

Preferred Qualifications

• Experience with Next Generation Sequencing (NGS) data formats (FASTQ, BAM, Matrix Market, HDF5)
• Proficiency with Haskell, R, or LaTeX

Benefits

• Competitive compensation package
• Membership in the Healthcare of Ontario Pension Plan (HOOPP)
• Flexible work environment
• Opportunities for professional development and promotion
• Access to transit and UHN shuttle services
• Various corporate discounts including travel, dining, and insurance

About the Company

University Health Network (UHN) is Canada’s #1 hospital and a global leader in publicly funded healthcare. As a top research hospital affiliated with the University of Toronto, UHN conducts world-class biomedical research across disciplines including oncology, neurosciences, and genomic medicine. The Schwartz Lab, located at the Princess Margaret Cancer Centre, focuses on developing novel computational methods to improve cancer diagnosis and treatment through precision medicine.