CANSSI Ontario Genome Data Science Postdoc 2027

CANSSI Ontario · Genome Data Science · University of Guelph Eligible Host

The CANSSI Ontario Postdoctoral Fellowship in Genome Data Science is a current 2027 funding route for early-career quantitative researchers. The fellowship provides up to C$50,000 per year for two years at a CANSSI Ontario partner university, and University of Guelph is a CANSSI member institution.

Genome Data Science Up to C$50,000 / Year 2 Years Deadline 1 Mar 2027

Current Status Eligibility How to Apply

Current status: OPEN. Current university funding listings show a 1 March 2027 application deadline for the CANSSI Ontario Postdoctoral Fellowship in Genome Data Science.

This is no longer the old Genome-Level Ecology vacancy. That specific Guelph postdoc closed in 2025. This page now covers the current CANSSI Ontario genome-data-science fellowship route that can be held at eligible Ontario partner universities, including University of Guelph.

CANSSI Ontario Genome Data Science Postdoctoral Fellowship 2027

The fellowship supports early-career investigators conducting full-time postdoctoral research in genomics and data science at CANSSI Ontario partner universities or affiliated research institutes.

University of Guelph is part of the CANSSI institutional network, making it a relevant potential host environment for eligible candidates who secure the required supervisory commitments.

Research Scope

Current programme descriptions emphasize genomics and data science, including areas such as:

statistical genetics;
genomic medicine;
environmental genetics;
multi-omic integration;
computational genomics;
genomic prediction tools;
human-computer interaction for genomic research; and
quantitative methods applied to genomic technologies.

Projects should be methodologically strong, innovative and generalizable rather than limited to one narrow predictive application.

Eligibility

Typical applicant backgrounds include:

statistics;
biostatistics;
computational biology;
bioinformatics;
computer science;
epidemiology;
genomics; or
another closely related quantitative discipline.

Applicants must undertake full-time postdoctoral research at a CANSSI Ontario member university or an affiliated research institute.

Candidates are responsible for identifying two faculty mentors from different academic units, with at least one mentor bringing relevant quantitative expertise such as statistics, biostatistics, epidemiology, computational biology, genomics or computer science.

Funding

Maximum annual support	C$50,000
Maximum duration	2 years
Maximum total support	Up to C$100,000
Host	CANSSI Ontario partner university or affiliated research institute

How to Prepare

Identify an eligible Ontario host institution and confirm that the university participates in the CANSSI network.
Secure two complementary faculty supervisors from different academic units.
Develop a genome-data-science project with a strong quantitative or methodological contribution.
Prepare the fellowship documents required by the current competition.
Confirm all local institutional review requirements if applying through University of Guelph.
Submit the complete fellowship application before the current 1 March 2027 deadline.

University of Guelph’s Research Alerts has previously circulated this CANSSI Ontario fellowship to its research community and confirms the university’s relevance as a participating host institution.

Frequently Asked Questions

Is the CANSSI Ontario Genome Data Science fellowship open?

Yes. Current university funding listings show a 1 March 2027 application deadline.

How much funding is available?

The fellowship provides up to C$50,000 per year for up to two years.

Can University of Guelph host the fellowship?

University of Guelph is a CANSSI member institution and is therefore relevant as a potential eligible host, subject to the current fellowship’s host and supervisor rules.

How many supervisors are required?

The programme requires two faculty mentors from different academic units, with complementary expertise.