Job description

Over the years, the Turcotte lab has gathered a comprehensive dataset encompassing whole-tumor and normal genome sequencing, whole-tumor transcriptomes, T-cell receptor sequencing, single tumor-infiltrating T-cell sequencing, spatial transcriptomes, multiplex immunofluorescence, multiparameter flow cytometry, digital 40X H&E images from a large cohort of patients who underwent surgery for colorectal cancer liver metastases.

In parallel, the lab has characterized T-cell recognition of these metastases and patient outcomes. To further unravel the factors that promote or hinder T-cell recognition of colorectal liver metastases, this immunogenomic and clinicopathological dataset requires in-depth analysis and expansion. The ultimate goal is to guide the development of more effective immunotherapies for this aggressive and common malignancy. To enhance analytical capabilities, the lab collaborates with AI experts, leveraging deep-learning models for more advanced insights.

Responsibilities

This role is focused on creating state-of-the-art computational frameworks for large-scale data manipulation and analysis, prioritising the development of tools that address the complexity of single-cell and spatial data.

Key responsibilities include:

• Designing and implementing novel bioinformatic tools and interfaces, primarily in R with extensions in Python, to handle the challenges of multiomic data integration
• Developing and expanding tidyomics (Hutchison et al., 2024), a modular software ecosystem for data manipulation and analysis, ensuring it meets the needs of complex datasets in biomedical research
• Creating and optimising pipelines to support harmonisation, scalability, and computational efficiency for analysing the cell data universe
• Incorporating cutting-edge methods, including aspects of artificial intelligence, to complement bioinformatic tools.

Qualifications

• PhD in Computational Biology, Bioinformatics, Computer Science, or a closely related field
• Demonstrable experience in analysing large-scale single-cell genomic data
• Proficiency in programming languages commonly used in computational biology and data science, such as R and possibly Python, with the ability to handle complex data analysis tasks. Please provide publicly available examples.
• A strong record of research, evidenced by publications in peer-reviewed journals or presentations at significant conferences, particularly in areas related to bioinformatics, computational biology, bioinformatics, or immunogenomics

Competitive benefits 

• Full-time position, 35 hours per week
• Flexibility of the schedule and work from home possible
• 1 year contract, renewable
• Competitive salary
• Start date: as soon as possible

To apply

Interested candidates should e-mail their cover letter and curriculum vitae, including three references to:
 mathieu.gigoux.chum@ssss.gouv.qc.ca

It is essential to attach your CV for your application to be considered.

Only successful candidates will be contacted for an interview.

The CRCHUM invites women, Aboriginals, visible minorities, ethnic minorities and people with disabilities to apply. The CRCHUM adopts a broad and inclusive definition of diversity that goes beyond applicable laws.

The CRCHUM thus encourages all people, regardless of their characteristics, to apply. In accordance with Canadian immigration requirements, please note that priority will be given to Canadian citizens and permanent resident.