Postdoctoral fellow of computational cancer biology -

University Health Network and Ontario Institute for Cancer Research
Job Type:
  • Postdoctoral
Degree Level Required:
PhD, PhD
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Postdoctoral fellow of computational cancer biology -

The OICR team is growing quickly. We are innovative, dedicated professionals who bring expertise to each of our roles. We are looking for individuals interested in being part of a culture of excellence that will result in Ontario being recognized internationally as a leading jurisdiction for cancer research. Launched in December 2005, OICR is an independent institute funded by the Government of Ontario through the Ministry of Research and Innovation. OICR has a diverse workforce and is an equal opportunity employer. For more information about OICR, please visit the website at Drs. Bhat and Reimand will consider highly motivated and creative candidates with a recently obtained Ph.D. degree. This is a unique opportunity to perform independent projects within a translational program, and significant potential for research productivity. Position is available immediately.


• Integrative analysis of multi-dimensional cancer genomics datasets using statistical and machine learning approaches; • Preprocessing and quality assessment of raw –omics data • Development of innovative computational methods and open-source bioinformatics software; • Visualization and interpretation of –omics data with pathway and network information; • Writing peer reviewed papers and grant proposals.


REQUIREMENTS • Highest graduate degree (PhD or equivalent). Degree in bioinformatics, computational biology, statistics, computer science or related fields are strongly preferred • Strong scientific publication record in peer-reviewed journals on bioinformatics and/or cancer research; • Strong understanding and interest in molecular biology, genomics, and cancer; • Practical knowledge of basic statistics; machine learning skills are a definite plus; • Familiarity with the Linux or MacOSX environment, shell scripting and system tools; experience with high performance computing is an asset; • Minimum 3 years of experience with programming and data analysis in R, Python, Perl, Matlab or similar; • Minimum 3 years of experience with bioinformatics resources, databases, tools and common standard formats; • Minimum 3 years of experience in analysing next-generation sequencing and/or microarray data; • Ability to work independently as well as part of a fast-paced and collaborative team; • Excellent verbal and written communication skills in English.

  • How to Apply

    Please send a CV, three letters of recommendation, and a research statement to both and

Additional Information

This represents a unique opportunity to augment bioinformatics and computational biology skills in cancer research to address clinically relevant questions in collaboration with a computational biologist and clinician-scientist. Dr. Bhat is a Hepatologist and Clinician-Scientist at UHN’s Multi Organ Transplant Program and Toronto General Research Institute. Her research program employs a bench-to-bedside paradigm in liver cancer research that connects clinical outcomes with basic research using bioinformatic analysis of ‘omic datasets (e.g., transcriptomic, miRNA, methylation, intestinal microbiome) from patient samples, followed by in vitro and in vivo validation. Specific topics of interest are Hepatocellular Carcinoma (HCC), Non-Alcoholic Steatohepatitis (NASH) and liver regeneration in the setting of liver transplantation. Dr. Reimand is a principal investigator of the Computational Biology Program at OICR. The Reimand lab focuses on integrative multi-omics data analysis of multiple cancer types to understand the genetic mechanisms of cancer, its molecular biomarkers and vulnerabilities for therapy development. We also develop novel analytical methods using statistical and machine-learning techniques. The research questions that drive our lab include the following: How to identify cancer driver mutations and their mechanistic impact using whole-genome sequencing data and other -omics information? How are biological pathways and molecular interaction networks altered by mutations, gene regulation, epigenetic modifications and DNA rearrangements? Which genes are promising targets for future drugs, and how can we repurpose existing drugs to treat cancer? How to build computational models, bioinformatics software and novel visualisations to integrate complex multi-dimensional datasets and discover new knowledge?