Diagnostic Bioinformatician

Toronto, QC, Canada
Job Type:
  • Programmer/Developer
Degree Level Required:
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Diagnostic Bioinformatician

Position: Diagnostic Bioinformatician
Site: MaRS Centre, Toronto
Department: Diagnostic Development
Reports To: Director, Diagnostic Development
Salary: Commensurate with level of experience
Hours: 35 hours/week
Status: Full-time, Temporary (one year)


• Preprocessing, processing and interpreting large next generation sequencing data sets to quantify gene expression, copy number aberrations and simple somatic mutations;
• Mining data sets for biomarkers that stratify patients according to their risk of disease progression and/or predict patient response to specific therapies;
• Exploring external biological databases, suggesting integration approaches and building prototypes to evaluate and fine-tune integration plan;Developing tools for data quality control, data validation and reporting;
• Interacting with the Director to design and develop bioinformatics and statistical algorithm approaches for clinical diagnostics. The incumbent will be co-mentored by a Bioinformatics PI;
• Liaising with other OICR experts in next generation sequencing, bioinformatics, and biostatistics to validate approaches;
• Preparing documentation for data specifications and analysis workflows;
• Participating in publications, grant writing and program funding review.


Required • PhD or post-doctorate in computational biology/bioinformatics or related field with 3-5 years professional experience;
• Knowledge of genomics, molecular and/or cancer biology;
• Experience with the analysis of next generation sequencing data;
• Experience with bioinformatics resources, databases, tools and common standard formats used in NGS;
• Strong scripting skills (R/python/perl), expertise in a statistical environment (matlab or R), and comfort working in Linux environment;
• Experience in biostatistics, particularly survival or Bayesian techniques;
• Excellent writing and communication skills;
• Experience with meeting publication, grant and experimental deadlines;
• Ability to work independently and mentored by our Informatics team.

• Experience with and in-depth knowledge of data modeling;
• Experience in machine-learning methods;
• Experience with clinical trials an asset;
• Previous experience in developing algorithms that have been implemented in a clinical diagnostic test highly preferred;
• Post-graduate research work in network modelling of cancer cell signaling networks, cancer heterogeneity and transcriptional regulatory networks;
• Previous experience working with Nanostring data is a plus;
• Data-visualization capabilities for large datasets.