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Postdoc in Manufacturing as a Service: Supporting the management of associated quantitative operations

  • On-site
    • Nantes, Pays-de-la-Loire, France
  • Informatique

Job description

Internationally recognized generalist engineering school of the IMT (Institut Mines-Télécom), a leading French engineering school (Technological University), IMT Atlantique aims to support transitions, train responsible engineers, and use scientific excellence to serve teaching, research, and innovation.

The Automation, Production, and Computer Science Department (DAPI) is conducting research projects in tight collaboration with the industry to create adaptable industrial systems, optimizing resource usage to achieve a sustainable environment. It relies on a large spectrum of fundamental and applied skills in mathematics, operations research, computer science, robotics, and automation.


ACCURATE is a Horizon Europe project dedicated to reshaping the European manufacturing landscape. The project aims to increase the competitiveness of manufacturing companies and value chains and to allow them to thrive in the midst of disruptions, by leveraging the Manufacturing as a Service (MaaS) paradigm. Manufacturing as a Service aims to improve responsiveness, flexibility, and scalability by satisfying on-demand needs (including production assets, goods, data, and software) through shared manufacturing resources offered as services. The area of interest of the proposed postdoc is structured around MaaS-related quantitative operations management, ensuring horizontal connectivity between shared resource providers and consumers, and supporting vertical integration of relevant data and decisions from the (global) MaaS level to (local) internal supply chain planning level.


Under the functional responsibility of the head of the DAPI department and in collaboration with the ACCURATE project team, the objectives of this postdoctoral fellowship are to:

1. Develop and evaluate the capabilities of a MaaS framework covering multiple supply chains by leveraging data space technologies, federated learning and analytics, and digital twins;

2. Disseminate research results in peer-reviewed journals, conferences, and other events.



Job description for more information

Job requirements

Minimum education and/or experience required:

  • ● PhD obtained less than 3 years before the hire date in Operations Research, Computer Science, or Industrial Engineering.

Essential skills, knowledge, and experience:

  • Strong background in Operations Research and, in particular, Combinatorial Optimization and Optimization under Uncertainty;
  • Proficiency in programming languages;
  • Proficiency in spoken and written English.

Abilities and skills:

  • Initiative and Autonomy
  • Team spirit
Deadline for application : 2025, January 19th

Starting date : March or April 2025

Interviews : end of January / beginning of February

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