Bioinformatics​/Data Science Analyst

Company Description

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.

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

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.

• 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

• 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…