Staff bioinformatician

Princess Margaret Cancer Centre - UHN
Toronto, ON, Canada
Job Type:
  • Staff
Degree Level Required:
PhD preferred, excellent candidates with MSc also considered
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Staff bioinformatician

The selected candidate will work closely with computational biology post-docs, research technicians and our clinical research coordinator. Within our academic environment, this position allows to make a significant contribution to cancer research and directly impact on our patients’ lives, by nature of our strong ties to the clinic. This position will also provide ample opportunities for professional development, for research planning and strategy, and for dissemination of findings at national and international meetings.


The individual will be responsible for maintaining large omics datasets, deploying state-of-the-art computational tools and developing methods, if needed. The individual will also be responsible for ensuring reproducibility of findings, presenting results to internal and external stakeholders and supervising more junior colleagues.


• Graduate degree in bioinformatics, computer science or statistics. • Minimum of 2 years related experience post graduate degree. • Strong computational skills. • Strong background with Unix/Linux, Perl and/or Python. • Advanced knowledge of NGS platforms and datatypes (FASTQ, BAM, VCF, MAF). • Experience with analysis of targeted, exome or genome sequencing data. • Experience with the integration of large-scale omics datasets. • Prior experience with cancer genomics is required. • Solid skills in statistical analysis (ANOVA, regression, clustering, phylogenetics, survival). • Expertise with R and Bioconductor. • Experience with machine learning and data modelling. • Excellent communication skills. • Willingness to work in a team environment. • Strong publication record.

Additional Information

The Princess Margaret Cancer Centre is one of the top 5 cancer centres in the world. We are a teaching hospital within the University Health Network and affiliated with the University of Toronto, with the largest cancer research program in Canada. This rich working environment provides ample opportunities for collaboration and scientific exchange with a large community of clinical, genomics, computational biology and machine learning groups at the University of Toronto and associated institutions, such as the Ontario Institute of Cancer Research, Hospital for Sick Children and Donnelly Centre.