Open-Rank Academic Position in Optimization & Learning for Decision Systems

About the role

The Center for Operations Research and Econometrics (CORE) at UCLouvain invites applications for two open‑rank academic positions in Operations Research. One focuses on Optimization and Learning for Data‑Driven Decision Systems, the other on Quantitative Supply Chain Management. Successful candidates will develop internationally visible research programmes, supervise doctoral students, publish in top journals, and collaborate with interdisciplinary teams within LIDAM, CORE and ICTEAM.

Key responsibilities

• Develop and lead a research agenda in advanced optimization and data‑driven decision making.
• Publish high‑impact papers in operations research, mathematical programming and machine learning.
• Supervise PhD students and contribute to teaching activities.
• Participate in academic events, secure research funding and foster collaborations across institutes.
• Address complex supply chain design, planning and operational problems using mathematical programming.

Required profile

• PhD in Operations Research, Applied Mathematics, Computer Science or a related field.
• Strong record of research publications in relevant areas.
• Ability to work in an interdisciplinary research environment.
• Experience with both theoretical and applied aspects of optimization.

Required skills

• Advanced optimization methods: linear, integer, stochastic, robust, distributionally robust, chance‑constrained.
• Predictive and prescriptive analytics, forecasting‑to‑decision frameworks.
• Learning‑integrated decision frameworks: predict‑then‑optimize, decision‑focused learning, reinforcement learning.
• Algorithmic decision models combining mathematical programming with AI techniques.
• Statistical and econometric methods for uncertainty modelling.

What we offer

• Opportunity to work in a renowned international research institute.
• Access to interdisciplinary labs and collaborative networks.
• Support for research funding and academic development.