Fully Funded PhD in Operations Research and Machine Learning in Montreal Université du Québec à Montréal in Canada

Fully funded PhD opportunities are available in Montreal, Canada, at Université du Québec à Montréal (UQAM) in the intersection of Operations Research and Machine Learning. The research group is looking for motivated doctoral candidates to work on optimization and decision-making problems with applications in transportation, logistics, telecommunications, and revenue management.

Research topics include stochastic and robust optimization, reinforcement learning for improvement problems, discrete choice models, and large-scale optimization for dynamic planning problems. The positions are connected to major Montreal research centers such as CIRRELT and GERAD, and involve joint supervision with faculty from UQAM and other Montreal universities including HEC Montréal, McGill University, Concordia University, and Polytechnique Montréal.

Eligible applicants should have a Master of Science or equivalent in Computer Science, Operations Research, Applied Mathematics, or a related field. Strong programming skills are required, and experience in optimization, machine learning, or data analysis is considered an asset. A good command of written and oral English is expected; French is not mandatory.

The opportunity is described as fully funded for the doctoral program, with research support in an advanced international environment. The post does not specify an exact stipend amount. Flexible start dates are listed as September 2026, January 2027, or September 2027.

To apply, candidates should email their application package to [email protected]. The package should include a motivation letter, CV/biography, academic certificates or grade records, and letters of recommendation or referee contact details. Applications are accepted until the positions are filled.