Meta-analyses and big data approaches in spatial and behavioural ecology

Project Description

I am recruiting a Master's student (Fall 2027 start) to join the NORTH lab in the Département de biologie at the Université de Sherbrooke. Students can tailor their research across two themes:

(1) Meta-analyses: large-scale syntheses on a topic of the student's choice, from dispersal and behaviour to climate resilience, conservation interventions, or any other ecological or evolutionary theme. Ideal for those who enjoy identifying patterns across studies, asking big-picture questions, and working with data across systems.

(2) Big data: using cutting-edge movement datasets from global wildlife tracking networks (over 14 billion locations from 1,500+ species) to develop predictive models of animal responses to environmental change. Students will build skills in R, spatial analysis, and ecological modelling.

Minimum qualifications: Canadian citizen or permanent resident, admissible to the Maîtrise en biologie, with a minimum 3.55/4.3 GPA (FRQNT scholarship threshold). Applicants must commit to submitting an external scholarship application (e.g., NSERC CGS-M, FRQNT B1, Weston Family Award) during their first fall semester. Knowledge of French is not mandatory; English theses are permitted. The position is contingent on securing external funding.

Competitive applicants will also have a strong undergraduate GPA (a major factor in scholarship competitions), experience with R or Python, practice communicating science, and comfort sharing research with academic and broader audiences.

Application materials (single PDF, subject "Join@NORTH", emailed to aprilmartinig@hotmail.com): cover letter (max 1 page), unofficial transcripts with GPA clearly indicated, CV, a writing sample, and contact information for three references (two academic, one non-academic).

Funding offered

To be discussed

$20,000 to $27,000 per year for 1 to 2 years

The last update was on 19 June 2026. The University reserves the right to modify its projects without notice.