Junior Bioinformatician

Deep Genomics
Job Location
Toronto, ON
  • Leading role in developing the future of genomic analysis and therapy
  • Inspiring, creative, and fast-moving startup work environment in downtown Toronto
  • Competitive compensation package
Job Description

Deep Genomics is a Toronto based startup aiming to revolutionize genome-based therapeutics using machine learning. It was founded by a team of scientists from the University of Toronto and is led by Dr. Brendan Frey, a world-leading researcher in the area of machine learning and genome biology. We are seeking a highly motivated junior bioinformatician with solid scripting skills to help with tasks like variant annotation, genomics data-set integration and other tasks. The position will report directly to the Director of Molecular Genetics and will involve close interactions with other company members.

  • BSc or MSc in Computer Science, Bioinformatics or related fields
  • Understanding of basic concept of molecular biology and human genetics
  • Solid knowledge of Python and Unix shell, some knowledge of R


Preferred but optional qualifications:

    • Experience with (human) genomics data
    • Familiarity with genetic variant annotation resources (e.g. RefSeq, Annovar, dbSNP, SIFT, UCSC genome browser and tables)
How to Apply

To apply for this position, please follow this link: 


About Our Organization

Founded in 2015, Deep Genomics brings together world-leading expertise in machine learning and genome biology. We’re inventing a new generation of computational technologies that predict what will happen within a cell when DNA is altered by genetic variation, whether natural or therapeutic.

Our clients and partners use our technology to discover and design diagnostics and therapies in computers, before they even reach the lab. Deep Genomics addresses the following needs:

  • Target bio-marker discovery
  • Interpretation of genetic variation
  • Genome-based therapeutic development
  • Molecular diagnostics and carrier screening
  • Risk assessment for complex disorders


Because our system models fundamental aspects of molecular biology, it can be used for any variant and any disease.

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