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 groundwater research related to the impacts of wildfires on water resources, combining hydrological modeling, machine learning, and hydrogeochemical analysis. The selected student will contribute to interdisciplinary work involving field sampling, advanced hydrogeochemical analysis of nutrients and contaminants, and hybrid deep learning–numerical hydrogeological models.

Research interests and keywords include groundwater, hydrogeology, hydrological modeling, machine learning, deep learning, hydrogeochemical analysis, remote sensing, GIS, geospatial modeling, and environmental science.

Minimum requirements: a Master’s degree in Hydrogeology, Environmental Engineering, Civil/Water Resources Engineering, or a related field; admissibility to UQAT Graduate Studies; strong motivation, independence, and interest in interdisciplinary environmental research.

Preferred background includes Python programming, remote sensing, GIS, geospatial modeling, and familiarity with hydrological/geochemical tools such as PHREEQC and MODFLOW. Prior research experience and peer-reviewed publications are also valued.

The position starts in Winter 2027, subject to UQAT graduate admissions deadlines. The application deadline is June 30, 2026.

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