You have a PhD in Operations Research, Operations Management, Applied Mathematics, Computer Science, Industrial Engineering, Management Engineering, or a closely related quantitative field.
You have a proven track record in university teaching, with evidence where possible by formal evaluations.
You have a strong and independent research track record, with publications, or clear potential to publish, in leading international journals in operations research, optimization, or quantitative management science. Experience in securing competitive research funding and supervising doctoral students will be considered a strong asset.
You have supplemented this with an extended stay or significant experience abroad, outside the institution that awarded your doctorate.
You are comfortable working as part of a team of academics and integrate research results into your teaching. You are capable of conducting high-level scientific research, from obtaining funding to team management. You are creative, open to pedagogical innovation and multidisciplinary.
You can communicate in French and English. If this is not the case, you undertake to acquire a command of these two languages within two years of taking up your position. Knowledge of other languages is an asset.
You will bring expertise in the modeling and optimization of supply chain systems, with a research identity anchored in the decision problems that characterize supply chain design, planning, and operations.
Your are able to combine methodological rigor in mathematical programming with a deep understanding of supply chain structures, incentives, and operational realities, and who is potentially able to integrate optimization with statistical and data-driven approaches to support evidence-based decision-making in complex supply environments.
Strong expertise in mathematical optimization and algorithmic decision-making is essential, while experience in data-driven analytics for supply chain systems is considered a strong asset.
Experience engaging with industry or real-world supply chain data is considered an asset when it is grounded in and contributes to the development of quantitative models and algorithmic methods for Supply Chain Management.
You will be expected to become an active and contributing member of the research community of CORE and, more broadly, of LIDAM, enriching its methodological culture with a research agenda at the intersection of operations research and quantitative management science, with clear supply chain identity and application depth.
