Dear all,
We are pleased to announce a fully funded PhD position at the LIMOS
Laboratory, University of Clermont Auvergne (France), starting around
September 2026, on the topic of Optimization for Sustainable
Remanufacturing Supply Chains.
Project Overview
Remanufacturing plays a crucial role in the circular economy by extending
product lifecycles, reducing waste, and improving resource efficiency. This
PhD position is part of a broader research initiative aimed at optimizing
remanufacturing-oriented reverse supply chains, integrating production
scheduling and inventory-routing decisions in complex, uncertain
environments involving multiple stakeholders (3PLs, retailers,
remanufacturers, etc.).
The PhD will focus on the Remanufacturing and Inventory Routing Problem
with Pickup and Delivery (RIRP-PD), incorporating Corporate Sustainability
Rules (CSR) with a special emphasis on human factors (stress and fatigue at
the plant level) and environmental indicators (CO2 emissions from
transportation).
A key challenge is to balance economic performance, workload, time, and
environmental impact while solving interconnected subproblems, inventory
routing, pickup and delivery, and job shop scheduling.
The project includes:
- Modeling a multi-stage problem involving pickup, job shop scheduling
with resource constraints, and delivery with time windows.
- Developing mathematical models and metaheuristics for sequential and
integrated problem solving.
- Studying multi-period variants, inventory strategies, labor workload
constraints, and CO2 emissions.
- Each major research step is expected to lead to publications in
international conferences and journals.
Candidate Profile
We are looking for a highly motivated PhD candidate with strong analytical
and programming skills.
Required:
- Master’s degree in Operations Research, Applied Mathematics, Industrial
Engineering, Computer Science, or related fields;
- Strong programming skills (C++, Python, or Java);
- Knowledge of: Mathematical modeling, especially Mixed Integer
Programming (MIP); Solvers such as CPLEX or Gurobi; Heuristics and
metaheuristics;
Appreciated (not mandatory):
- Experience with exact methods (Branch-and-Bound, Branch-and-Price,
decomposition approaches);
- Interest in sustainability, circular economy, or human-centered systems;
- Familiarity with machine learning for optimization.
Application Documents
- Detailed CV
- Motivation letter
- Academic transcripts (Master’s degree or equivalent)
- Optional: recommendation letters
For applications and inquiries, please contact:
- Prof. Philippe Lacomme (philippe.lacomme@uca.fr)
- Prof. Katyanne Farias (katyanne.farias_de_araujo@uca.fr)
- Prof. Flavien Lucas (flavien.lucas@imt-nord-europe.fr)
Best regards,
Katyanne FARIAS