Integrated Learning and Optimization for Maintenance Planning of Large-Scale Partially Observable Systems

Type de recrutement
CentraleSupelec, Université Paris Saclay
Fin de l'affichage
Détails (fichier)

The chair of Risk and Resilience of Complex Systems (RRCS), Industrial Engineering Laboratory (LGI) within CentraleSupélec at the University of Paris Saclay is looking for a doctoral student working on large-scale Partially Observable Markov decision-making problems, applied to maintenance planning of complex multi-unit industrial systems, such as fleets of wind farms, high-speed trains, and telecommunication antenna/data-centers. The chair RRCS is funded by three prominent actors of the French industry: EDF (Power supply provider), Orange (Telecom), and SNCF (Railway).

The Ph.D. candidate will be directed by Associate Professor Yiping Fang, Professor Anne Barros, and Associate Professor Adam F. Abdin. She/he will have the opportunity to build a rich network by interacting with the three partners at the top management level and the operational ones. She/he will also have great opportunities to stay in several other prestigious research institutes or universities in France or abroad, including with other laboratories at CentraleSupélec (especially the Laboratory of Signal and Systems and the Mathematics and Informatics Lab), INRIA Paris, École Normale Supérieure Paris, Delft University (Netherland), Rutgers University (USA), University of New South Wales (Australia), and the University of Edinburgh Business School (UK) within the collaboration network of the Chair project.

Candidate Profile

The candidate will work within an interdisciplinary project, at the interface of operations research, machine learning, and engineering, for which we expect that:

  • You are proactive and highly motivated, having an MSc degree (or equivalence) in a quantitative discipline (such as applied mathematics, computer science, or engineering) from a recognized university.
  • You have a strong background in quantitative modeling (statistics, mathematical programming and optimization, and machine learning) and computer programming.
  • Professional command of English (both written and spoken) is mandatory. French is not mandatory, but surely a plus.
  • You will need to enjoy working in a dynamic and international environment with other doctoral students and postdocs.

How to apply?

We look forward to receiving your application with the following documents compressed in one PDF file and sending it as an attachment to with the title “[Your name]-RRCS 2023 PhD Application”:

  • Curriculum Vitae, max. two pages
  • Motivational Letter, max. two pages
  • Transcript of academic records (including detail of grades and rankings when available)
  • Two reference letters with contact details

Please note that the position will start as soon as possible, and we exclusively accept applications submitted through before June 15, 2023.

Further information about the RRSC team and LGI Laboratory can be found on the website. Questions regarding the position should be directed to Dr. Yiping FANG (, Dr. Adam F. Abdin (, and Professor Anne Barros ( (no applications).