PhD in Groundwater Research: Hydrological Modeling, Machine Learning, and Hydrogeochemical Analysis at Université du Québec en Abitibi-Témiscamingue Université du Québec en Abitibi-Témiscamingue in Canada

Université du Québec en Abitibi-Témiscamingue (UQAT) is recruiting a PhD student in the Groundwater Research Group (GRES) at the Institut de recherche en mines et en environnement (IRME).

The project focuses on hydrological modeling, machine learning, and hydrogeochemical analysis to improve understanding of how wildfires affect water quantity and quality. The selected student will contribute to interdisciplinary research involving field sampling, advanced hydrogeochemical analysis of nutrients and contaminants, and hybrid deep learning–numerical hydrogeological models.

Research areas / keywords: groundwater, hydrogeology, environmental science, civil/water resources engineering, machine learning, GIS, remote sensing, geospatial modeling, PHREEQC, MODFLOW.

Eligibility: applicants should hold a master’s degree in hydrogeology, environmental engineering, civil/water resources engineering, or a related field. Admission to UQAT Graduate Studies is required. The post also highlights strong motivation, independence, and interest in interdisciplinary environmental research. Preferred experience includes Python programming, remote sensing, GIS, geospatial modeling, hydrological/geochemical modeling tools, and prior research/publication experience.

Funding: no explicit funding or stipend details are stated in the post.

Deadline: June 30, 2026. The position is for Winter 2027, subject to UQAT graduate admissions deadlines.

How to apply: email Dr. Rahim Barzegar at [email protected] with the subject line “PhD application – winter 2027”. Attach a one-page statement of interest, CV, and academic transcripts.