Bioinformatics Research Analyst

Princess Margaret Cancer Centre / University Health Network
Toronto, ON, Canada
Job Type:
  • Staff
Degree Level Required:
Masters, PhD
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Bioinformatics Research Analyst

A full-time position is available at the Princess Margaret Cancer Centre in Toronto, Canada. The successful candidate will support bioinformatics/computational biology efforts of the principal investigators in our PMCC Cancer Biology and Imaging program. The successful candidate will help organize, plan, analyze, and interpret the results from a variety of exciting projects that are currently ongoing. The successful candidate will help analyze and interpret RNA-seq, Chip-Seq, whole genome sequencing, chromatin conformation capture, and single-cell RNA-sequencing data sets generated from a variety of cellular and murine model systems.

The successful candidate will have access to our high-performance computing infrastructure and will work with world class Scientists/Bioinformaticians in Toronto.

In an exciting and fast paced place to work, we are looking for that ideal mixture of technical skills, biology, and creativity to grow and sustain bioinformatics efforts at one of the leading cancer research centres in the world. Excellent salary and benefits will be provided


The successful candidate: • Will work closely with a number of principal investigators working on cancer biology • Must have a strong sense of teamwork, be highly motivated, possess excellent organizational, problem-solving and communication skills (both verbal and written). • Will organize, plan, analyze, and interpret the results • Provide help with publication of bioinformatics data


Candidates must have: • A MSc or higher degree • Experience in computer science, bioinformatics and biostatistics/statistics as well as hands-on experience in the use of Unix/Linux command line, R, and statistical approaches (including Machine Learning techniques) to analyze, visualize and interpret genome-scale data sets. • Preferred but not required are expertise in a scripting language (Python, Perl), best practices for software development (e.g. version control) and the use of high-performance computing systems (e.g. TORQUE) for analyzing large data sets. • Hands-on experience processing and analyzing next-generation sequencing data, ATAC-seq and RNA-Sequencing data analysis is preferred. • Experience with single cell sequencing data (e.g. Fluidigm C1, 10X, Dropseq) and tools (e.g. Seurat, SCONE, SINGuLAR) is a strong plus. • Relevant publications in any of the fields of cancer, genomics, statistics, or computational algorithms or tool development • The successful candidate needs to be very familiar with cancer biology

  • How to Apply

    Applicants should respond by email with a curriculum vitae, cover letter and contact of three referees to