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Bioinformatics/Data Science Analyst

University Health Network

Toronto, ON

Job typeFull-time
SpecialtyTechnical
Compensation$35.35 – $53.03/hour
PostedJul 17, 2026

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Location620 University Avenue, Toronto, ON, CAOpen

eHealth role summary

Role is a Senior Bioinformatics Analyst working on cancer genomics and bioinformatics: designing/implementing high-throughput sequencing data pipelines, analyzing WGS/RNA-seq/single-cell data, developing computational methods, and managing HPC — all health-related informatics work.

About this role

Union: Non-Union
Number of Vacancies: 1
New or Replacement Position: New
Site: Princess Margaret Cancer Centre
Department: Research
Reports to: Principal Investigator 
Salary Range: $35.35 - $53.03 per hour
Hours: 37.5 Hours Per Week
Shifts: Monday - Friday, Days
Status: Temporary Full-time (1 year contract)
Closing Date: August 16, 2026

Position Summary:
A Senior Bioinformatics Analyst position is available in Toronto, Canada, in the laboratories of Dr. Tomohiro Aoki and Dr. Robert Vanner at the Princess Margaret Cancer Centre, University Health Network; one of the top five cancer research centers in the world. The research focus is basic/translational research in cancer immunology and cancer genomic field in the lymphoid malignancy and clonal hematopoiesis. With access to our world-class computational infrastructure, and in collaboration with world-leading scientists locally and abroad, the successful candidate will help organize, plan, analyze, and interpret the results from a variety of exciting large genomic cohort analyses that are currently ongoing.

Duties:

  • Design and execute experiments to study the pathogenesis, molecular mechanism and treatment resistance mechanism, and tumor-microenvironment interaction in lymphoid malignancy
  • Analyze and interpret molecular analyses from DNA/RNA sequencing data (including single cell sequencing, whole genome sequencing, circulation tumor DNA analyses, methylation profiling)
  • Analyze and interpret spatial analyses (e.g. protein level and transcriptional level)
  • Develop and oversee high-throughput data pipelines, including data from many new single-cell technologies such as scRNA-seq, scATAC-seq, scMultiome-seq, and Visium/CosMx spatial transcriptomics.
  • Analyze any sequencing data using established pipelines.
  • Develop new computational methods to integrate and interpret multi-omics data.
  • Assist and collaborate with internal and external researchers in interpretation of sequencing data.
  • Contribute to the codebase, development, and support of open-source software packages.
  • Help to manage lab servers and computational infrastructure.
  • Document and present results in written or oral reports to other lab members.
  • Work collaboratively with other research team members and external collaborators.
  • Participate in multidisciplinary projects combining biochemistry, structural biology, and computational methods
  • Stay updated with the latest research in cancer genomics, cancer immunology and lymphoma biology.
  • Review and summarize relevant scientific literature to inform experimental design and data interpretation
  • Prepare manuscripts for publication in scientific journals
  • Present research findings at national and international conferences, seminars, and workshops
  • Assist in writing grant proposals to secure funding for ongoing and future research projects.
  • Mentor and supervise graduate and undergraduate students involved in related research projects
  • Provide guidance on experimental techniques and data analysis

Qualifications

  • B.Sc., M.Sc. or Ph.D. in bioinformatics, computer science or recognized equivalent in Health and or Science-Related Discipline or a related field
  • At Minimum, 1 years related experience r
  • Programming skills in R, Python, BASH, TensorFlow or similar.
  • Experience working in a Linux environment and the use of high-performance computing systems (i.e. Slurm) for analyzing large datasets
  • Adhering to best practices for software development (version control, GitHub)
  • Demonstrated exposure to NGS data analysis and datatypes (FASTQ, BAM, VCF, etc) including analysis of targeted, exome or genome sequencing data
  • Hands-on experience with cancer genomic analyses including WGS, RNA-seq, ATAC-seq, single cell RNA-seq, or similar, is preferred
  • Experience in cancer genomic study preferred
  • Team oriented with excellent written and verbal communication skills.
  • Training in statistics or machine learning preferred.
  • Ability to work effectively in a collaborative research environment
  • Experience in mentoring students and junior researchers
  • Solid skills in statistical analysis (ANOVA, regression, clustering, phylogenetics, survival).
  • Experience with machine learning and data modelling is an asset
  • Excellent communication skills
  • Willingness to work in a team environment

Additional Information

Why join UHN?

In addition to working alongside some of the most talented and inspiring healthcare professionals in the world, UHN offers a wide range of benefits, programs and perks. It is the comprehensiveness of these offerings that makes it a differentiating factor, allowing you to find value where it matters most to you, now and throughout your career at UHN.

  • Competitive offer packages
  • Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP https://hoopp.com/)
  • Close access to Transit and UHN shuttle service
  • A flexible work environment
  • Opportunities for development and promotions within a large organization
  • Additional perks (multiple corporate discounts including: travel, restaurants, parking, phone plans, auto insurance discounts, on-site gyms, etc.)

Current UHN employees must have successfully completed their probationary period, have a good employee record along with satisfactory attendance in accordance with UHN's attendance management program, to be eligible for consideration.

All applications must be submitted before the posting close date.

UHN uses email to communicate with selected candidates.  Please ensure you check your email regularly. At University Health Network (UHN), artificial intelligence technologies may be used to assist in the screening, assessment, and selection of candidates for this position.

Please be advised that a Criminal Record Check may be required of the successful candidate. Should it be determined that any information provided by a candidate be misleading, inaccurate or incorrect, UHN reserves the right to discontinue with the consideration of their application.

UHN is an equal opportunity employer committed to an inclusive recruitment process and workplace. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their requirements known.

We thank all applicants for their interest, however, only those selected for further consideration will be contacted.