Context

Digital twins are virtual representations of real-world products, systems, or processes, enabling simulation, integration, testing, monitoring, and maintenance. They play a pivotal role in optimizing complex systems across a wide range of domains, from industrial manufacturing and energy to environmental monitoring and healthcare.

The Engineering Digital Twin EDT program, funded by the France 2030 investment plan, is a national initiative aimed at advancing the foundations of digital twin engineering in France and Europe. By bringing together leading academic and industrial partners, EDT seeks to strengthen the bases for the design, use, and deployment of digital twins, addressing key open challenges in model hybridization, composability, development methodologies, digital coupling, and human–twin interaction.

In the long term, digital twins should be able to exist for a period that could exceed that of their reference system (a factory, a product, a territory, etc.). Digital twins must therefore be designed and built to be maintainable, scalable, and interoperable, based on existing information, and to collect all future information.

To this end, we would like to propose an approach to building digital twins based on principles similar to those of DevOps. In other words, principles that enable continuous improvement of the various building blocks that make up the digital twin, while ensuring the interoperability and consistency of the information (data and models) collected.

We are seeking a highly motivated postdoctoral researcher to join our team working on the methodological aspects of digital twin development.

Objectives

The mission of the position is to propose innovative methodological approaches for the development, implementation and industrialization of digital twins. The task consists of studying what is currently being done in the field and proposing innovative approaches that allow researchers and PhD students in the EDT program to use tried-and-tested methods and tools.

This methodology, will be accompanied by a digital twin development lifecycle model, including traceability, evolution, analysis, and change impact management . To this end, case studies relying on existing digital twins (models and data) will be central to the work and cover a wide range of uses.

The position will be closely collaborating with the engineering teams of the AT3.

Responsibilities

• Contribute to research on Project PC3
• Collaborate with interdisciplinary research teams
• Publish research findings in high-impact journals
• Participate in project meetings and presentations
• Mentor and support PhD students in relation with the methodology

Work Environment

The PhD candidate will be co-supervised by Sophie Eberdold, UT2J and Marcos Didonet del Fabro, CEA List within UT2J-IRIT-SM@RT.

The candidate will benefit from a stimulating scientific and industrial environment of the highest level, with access to a national network of leading research institutions and industry partners, regular interactions with the broader EDT community through workshops, seminars, and joint demonstrators, and will be responsible for defining the early versions of Artemis, the program’s open software platform.

Application Process

Please submit your application including CV, cover letter, and contact information for three references.

What You Will Gain from This PhD

This postdoctoral offers the opportunity to:

• Develop highly sought-after skills in system modeling, real-time data processing, and collaborative innovation.
• Collaborate with leading partners (Inria, CEA, CNRS, etc.) and validate your research on real-world industrial use cases.
• Join a network of PhD candidates within the EDT program, fostering collaboration, peer support, and interdisciplinary exchanges.
• Contribute to an open-source platform (Artemis) and publish in international conferences and journals.
• Gain recognition in a rapidly growing field, with career prospects in academic research, industrial R&D, or entrepreneurship.

Upon completion, you will be positioned as a recognized expert in a key domain for industry and research, with diverse professional opportunities in France and internationally.

References

• Benoît Combemale, Pascale Vicat-Blanc, Arnaud Blouin, Hind Bril El Haouzi, Jean-Michel Bruel, et al.. Engineering Digital Twins: A Research Roadmap. EDTconf 2025 - 2nd International Conference on Engineering Digital Twins, Oct 2025, Grand Rapids, Michigan, United States. pp.1-7. ⟨hal-05223776⟩
• Gwendal Beaumont, Antoine Beugnard, Salvador Martínez, Christelle Urtado, Sylvain Vauttier, Towards Automating the Life Cycle Management of Digital Twins ER2025 - 44th International Conference on Conceptual Modeling, Oct 2025, Poitiers, France. pp.412-430, ⟨10.1007/978-3-032-08623-5_22⟩
• Tarek Alskaif, Önder Babur, Francis Bordeleau, Loek Cleophas, Benoît Combemale, et al., Evolution at the Core of Digital Twin Engineering EDTconf 2025 - 2nd International Conference on Engineering Digital Twins, Oct 2025, Grand Rapids, Michigan, United States. pp.1-6
• Judith Michael, Loek Cleophas, Steffen Zschaler, Tony Clark, Benoît Combemale, et al., Model‐Driven Engineering for Digital Twins: Opportunities and Challenges, Systems Engineering, 2025, 28 (5), pp.659-670. ⟨10.1002/sys.21815⟩
• Meriem Smati, Vincent Cheutet, Christophe Danjou, Jannik Laval, Digital Twin System of Systems: A Layered Architecture Proposal. MODELSWARD 2025: 273-279