McGill University
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1 month ago
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Fully Funded PhD in Functional Freshwater Ecology at McGill University McGill University in Canada
Degree Level
PhD
Field of study
Data Science
Funding
Fully funded PhD position. Includes training in freshwater ecology, functional ecology, spatial modelling, and biodiversity science. Part of the NSERC Alliance project 'Altered Lakes, Transformed Roles'.
Country
Canada
University
McGill University

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About this position
PhD position in Functional Freshwater Ecology at McGill University (Department of Biology, Canada). The project investigates how complex life cycles shape freshwater biodiversity, with a focus on how life-history strategies of freshwater insects influence community assembly and ecosystem responses across local habitats, watersheds, and continental gradients.
The research sits at the intersection of biology, environmental science, freshwater ecology, functional ecology, community ecology, biogeography, and statistics/data science. The position is linked to the NSERC Alliance project Altered Lakes, Transformed Roles and offers training in freshwater ecology, spatial modelling, and biodiversity science.
Eligibility highlights include a Bachelor's Honours or Master's degree in Biology, Ecology, Environmental Science, or a related field; strong quantitative analytical skills; proficiency in Python or R; field experience; and motivation to build data science skills. Helpful experience includes functional trait databases, dragonfly communities, spatial modelling, and hierarchical ecological models, plus an interest in biodiversity and environmental change.
This is a fully funded PhD opportunity. The post says applications are reviewed from July 2026 until filled, with a start in 2027. To apply, send a cover letter, CV, and transcript to [email protected].
Funding details
Fully funded PhD position. Includes training in freshwater ecology, functional ecology, spatial modelling, and biodiversity science. Part of the NSERC Alliance project 'Altered Lakes, Transformed Roles'.
What's required
Bachelor's Honours or Master's degree in Biology, Ecology, Environmental Science or a related field; strong quantitative analytical skills; proficiency in Python or R; field experience; motivation to develop data science skills. Desirable experience includes functional trait databases, dragonfly communities, spatial modelling, hierarchical ecological models, and interest in biodiversity and environmental change.
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