Université du Québec à Chicoutimi (UQAC)

Public research university in Québec, Canada, conducting research in engineering, environmental sciences, and artificial intelligence.

Homepage: https://www.uqac.ca/

Postdoctoral Researcher – Deep Learning for Groundwater Forecasting

Université du Québec à Chicoutimi (UQAC), Canada

A postdoctoral position is available at UQAC for a research project conducted in partnership with the Québec Ministry of the Environment (MELCCFP).

The project focuses on developing deep learning methods for groundwater-level forecasting, with particular attention to model generalization, uncertainty quantification, and interpretability.

Required qualifications:

• Completed PhD in Artificial Intelligence, Data Science, Computer Science, Applied Mathematics, or a related field.
• Strong, demonstrated expertise in deep learning, including the independent development, training, evaluation, and debugging of neural network models.
• Excellent Python programming skills, with substantial hands-on experience in PyTorch or TensorFlow.
• Ability to conduct research independently, with strong analytical and problem-solving skills.

Experience in time-series forecasting, transfer learning, or uncertainty quantification is highly desirable. Hydrology or hydrogeology knowledge is an asset, not a requirement.

Applications without demonstrated practical expertise in deep learning and Python will not be considered.

Position details:

• Location: Chicoutimi, Québec, Canada (on-site).
• Salary: CAD 60,000 gross per year.
• Duration: Up to 12 months, with an expected start in early 2027.
• The funded research project ends in February 2028.

Please send your application to avadombi@uqac.ca with the subject "Postdoctoral Application – Deep Learning".

Your application must include:

1. A CV with a list of relevant publications.
2. A brief description of a deep learning project you personally implemented, specifying your technical contributions.
3. Links to relevant code or other evidence of practical deep learning experience, if available.

Applications will be reviewed on a rolling basis. Only shortlisted candidates will be contacted.