Funded PhD Position in Community Ecology and Biogeography
The Community Ecology & Biogeography Lab at Concordia University, Montreal, is offering a funded PhD position focused on the ecological and evolutionary determinants of biological diversity. The lab investigates the maintenance and distribution of biodiversity, both in contemporary and historical contexts, with a particular interest in predicting how biodiversity will respond to global changes and understanding the impact of human-driven community reassembly on ecosystem processes. Research combines theoretical and empirical approaches, with a strong emphasis on field-based projects involving insects such as ants, dragonflies, and bees, and their roles in ecosystem functioning.
Key research areas include community ecology, biogeography, biodiversity, ecological networks, global change biology, species range dynamics, climate change, ecological modeling, spatial analysis, macroecology, insect ecology, soil arthropods, nutrient cycling, carbon storage, plant–pollinator networks, host–parasite networks, plant–microbial networks, evolutionary ecology, field ecology, quantitative ecology, and the use of R programming and large ecological datasets. Current research questions address the ecological and evolutionary determinants of species range limits and dynamics in the context of environmental changes, the assembly rules of ecological networks, and the role of ants and other soil arthropods in nutrient cycling and carbon storage.
The position is supervised by Professor Jean-Philippe Lessard and is based in the Department of Biology. The successful candidate will receive a stipend and have opportunities for teaching and research assistantships. The lab values diversity and inclusivity, welcoming applicants from the global south, LGBTQ+ community, and other underrepresented groups. Concordia University is located in the vibrant and multicultural city of Montreal, Canada.
Applicants should possess a strong academic background in ecology, biogeography, or evolutionary biology, proficiency in R or another scientific programming language, experience with large datasets and quantitative analysis, and ideally fieldwork experience in ecological or biodiversity studies. Additional assets include knowledge of ecological modeling, spatial analysis (GIS), mathematics applicable to quantitative ecology, understanding of insect physiology or biochemistry, previous scientific publishing experience, and motivation to secure external funding.
To apply, candidates should compile a single PDF including a cover letter, academic CV, unofficial transcripts, names and contact information of two referees, publications, and any other relevant documents. This should be sent to [email protected] with the subject line 'Community Ecology_Your name' by January 8, 2026. For further inquiries, contact Alisa Makusheva at the same email address.