More jobs:
Bioinformatics/Data Science Analyst
Job in
Toronto, Ontario, C6A, Canada
Listed on 2026-02-28
Listing for:
University Health Network
Full Time, Seasonal/Temporary
position Listed on 2026-02-28
Job specializations:
-
Research/Development
Research Scientist, Clinical Research, Data Scientist
Job Description & How to Apply Below
UHN is Canada’s #1 hospital and the world’s #1 publicly funded hospital. With 10 sites and more than 44,000 TeamUHN members, UHN consists of Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre, Toronto Rehabilitation Institute, The Michener Institute of Education and West Park Healthcare Centre. As Canada’s top research hospital, the scope of biomedical research and complexity of cases at UHN have made it a national and international source for discovery, education and patient care.
UHN has the largest hospital‑based research program in Canada, with major research in neurosciences, cardiology, transplantation, oncology, surgical innovation, infectious diseases, genomic medicine and rehabilitation medicine. UHN is a research hospital affiliated with the University of Toronto.
Job Description
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: $68,932 - $86,165 Annually
Hours:
37.5 Hours Per Week
Shifts:
Monday - Friday, Days
Status:
Temporary Full-time
Closing Date:
March 13, 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 centres in the world. The research focus is basic/translational research in cancer immunology and cancer genomic field in the lymphoid malignancy and clonal haematopoiesis.
With access to our world-class computational infrastructure, and in collaboration with world‑leading scientists locally and abroad, the successful candidate will help organise, plan, analyse, 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 tumour‑microenvironment interaction in lymphoid malignancy
Analyse and interpret molecular analyses from DNA/RNA sequencing data (including single‑cell sequencing, whole genome sequencing, circulating tumour DNA analyses, methylation profiling)
Analyse 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, sc Multiome‑seq, and Visium/Cos Mx spatial transcriptomics
Analyse 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 summarise 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 recognised equivalent in Health and or Science‑Related Discipline or a related field
Programming skills in R, Python, BASH, Tensor Flow or similar
Experience working in a Linux environment and using high‑performance computing systems (i.e. Slurm) for analysing large datasets
Adhering to best practices for software…
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