9 Jan 2026
Job Information
- Organisation/Company
IMT Mines Ales- Department
Human Ressources Department- Research Field
Engineering » Systems engineering- Researcher Profile
First Stage Researcher (R1)- Positions
PhD Positions- Country
France- Application Deadline
15 Feb 2026 - 01:00 (UTC)- Type of Contract
Temporary- Job Status
Full-time- Offer Starting Date
1 Apr 2026- Is the job funded through the EU Research Framework Programme?
European Union / Next Generation EU- Is the Job related to staff position within a Research Infrastructure?
No
Offer Description
Founded in 1843, IMT Mines Alès currently has 1,400 students (including 250 foreign students) and 380 staff. The school has 3 research and teaching centres of a high scientific and technological level, working in the fields of materials and civil engineering (C2MA), the environment and risks (CREER), artificial intelligence and industrial and digital engineering (CERIS). It has 12 technology platforms and 1,600 partner companies.
The person recruited will be involved in the Trusted Autonomous and Self-Adaptive Systems for Defence (SAACD) project. This project aims to overhaul the engineering and development of this type of complex system.
A SAACD can be defined at two levels:
- SAACD Component: This is a UAV made up of hardware and software sub-systems, capable of observing, predicting, deciding and reconfiguring itself to fulfil its mission (e.g. surveillance, detection, tracking, control, etc.). The integration of on-board AI requires new engineering methods, which are still poorly supported by digital twins.
- SAACD System of Systems (SdS): this corresponds to the assembly of several SAACD Components, in homogeneous swarms or heterogeneous packs to fulfil a common mission, e.g. monitoring a critical infrastructure.
Both must be designed to promote these autonomy and self-adaptation capabilities. Three major challenges have been identified:
- (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed to irrigate engineering processes and validate this design as early as possible;
- (P2) integrate a reliable and frugal embedded AI (limited to inference and/or also capable of learning, e.g. reinforcement learning) as one of the components of a SAACD. A component that facilitates, again with a demonstrable level of confidence, observation, prediction and the decision to adapt or partially reconfigure;
- (P3) Ultimately, aim for SAACD certification based on proof of validity and reproducibility.
The R&D questions concern :
- (For P1) "AI as a service" to enrich engineering: modelling of the changing, complex and uncertain environment (essentially for the purposes of assisting understanding, verification and validation) of the uncertain environment in which the SAACD Component or the SAACD SoS evolves;
- (For P2) "AI as a component" as a component in its own right of the SAACD, but which must reconcile frugality and reliability of the actions envisaged according to the situation encountered in this moving and unpredictable environment;
- (For P3) Exploit the Digital Twin Systems, integrating the AI contributions developed in P1 and P2, to optimise the simulations, certification, maintenance, training and piloting of the two types of SAACD.
This project will involve formalising and integrating the contributions of : (i) model-based and data-driven systems engineering (MBSE), (ii) embedded frugal (explainable and robust) AI, and finally (iii) advanced modelling, simulation and optimisation techniques in a complex uncertain environment for the design of a SAACD.
The working approach is based on four successive and iterative phases, making it possible to demonstrate the feasibility of the SAACD project. The person recruited will therefore be involved in each phase, which combines methodological, technological and experimental aspects, drawing on the expertise of SyCoIA's Lecturers/Researchers in MBSE/MBSSE, predictive analytics, autonomous decision-making, robust and explainable AI, and interoperable digital twins. These phases are summarised below:
- Phase 1 - Definition and modelling of use cases: M1-M3
- Phase 2 - AI services for engineering (AI-as-a-Service): M4-M8
- Phase 3 - Trusted frugal embedded AI (AI-as-a-Component) : M6-M11
- Phase 4 - Integration, demonstration and proof by digital twins: M10-M16
Where to apply
- Website
- https://www.imt-mines-ales.fr/
Requirements
- Research Field
- Engineering » Systems engineering
- Education Level
- PhD or equivalent
Skills/Qualifications
Your manager and the team in place will support you in developing your skills, while making the most of your experience and talents.
The person we are looking for will bring skills and experience in at least one, and preferably several, of the following R&D areas:
- Explainable AI (knowledge of the latest advances in explainability methods: intrinsic, simplification, counterfactual, etc.).
- Robust AI (knowledge of methods for quantifying uncertainty in deep learning or formal verification methods applied to deep learning)
- Embedded AI
- Reinforcement learning, supervised and unsupervised learning
- Distributed / decentralised command and control: synchronisation, coordination, adaptation, for example using multi-agent systems
- Decision support under uncertainty
- Modelling and simulation of the behaviour of complex systems
The successful candidate will need to acquire the necessary and sufficient skills for the needs of the SAACD project in the areas of Model-Based Systems Engineering and Digital Twin Engineering during the course of the project. He/she will organise, plan and trace the organisation of tasks, meetings and actions and will manage and contribute to the drafting of project deliverables.
Minimum level of training and/or experience required :
In addition to your degree, your personality will make the difference.
- Postgraduate doctorate in sections CNU 61 or 27
- Ability to strengthen at least one of the above research themes involved in the project
- Experience in research and development (industrial and/or academic other than related to the thesis itself)
Technical and cross-disciplinary skills required :
- Dynamic
- Autonomy
- Intellectual curiosity
- Ability to act as an interface between the Systems Engineering, AI and Simulation communities.
- Ability to contribute to the team's, centre's and school's project.
- Scientific output: quality and number of publications in recognised international journals
- Fluency in scientific English essential
Internal Application form(s) needed
FP - Postdoctoral researcher, SAACD project.pdf
English
(1.12 MB - PDF)
Download
Additional Information
Benefits
So join us and enjoy these many benefits:
- Generous vacation time
- On-site dining
- 75% of public transportation costs covered
- Sustainable mobility package for carpooling or cycling to work
- Stimulating innovation ecosystem (startups, students, research, businesses, etc.)
- Ideal environment for pursuing your passions (sea/mountains nearby)
Eligibility criteria
The position offered by IMT Mines Alès is a 15-month, full-time, public-law contract governed by the provisions of the management framework of the Institut Mines-Télécom, profession P, Post-doctoral fellow, category II.
This position requires national defence secret clearance. Obtaining this clearance is subject to an administrative enquiry and depends on the regulations in force. Only candidates who meet the legal requirements can be cleared and therefore recruited.
Salary: Your salary will be reviewed and determined on the basis of your experience and associated skills.
Selection process
A panel made up of several people will meet with you and ensure that you are in the best possible condition to make a success of this meeting.
Closing date for applications: 15/02/2026
Approximate date of the interview: 26/02/2026
Preferred starting date: 01/04/2026
- Website for additional job details
https://institutminestelecom.recruitee.com/o/post-doctorant-ou-post-doctorante-…
Work Location(s)
- Number of offers available
- 1
- Company/Institute
- IMT Mines Alès
- Country
- France
- State/Province
- Occitanie
- City
- Alès
- Postal Code
- 30100
- Street
- 6 Avenue de Clavières
- Geofield
Contact
- City
Ales- Website
https://www.imt-mines-ales.fr/- Street
6 avenue de Clavières- Postal Code
30100
STATUS: EXPIRED
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