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University, is recognized for its expertise in artificial intelligence and formal methods In this stimulating academic context, we will focus on the problem of explainability of artificial intelligence models
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disturbances, embedded constraints, and AI decision integrity in critical systems. This PhD aims to develop a unified methodology for evaluating and improving the robustness of embedded AI modules against
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physics, particularly those arising from renormalization-group methods. The successful candidate will collaborate with the principal investigator and other members of the group to invent, refine, and
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a collaboration between Inria and Mitsubishi Electric R&D Centre Europe (MERCE) within the FRAIME project on artificial intelligence and formal methods. The project explores, on the one hand, how
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Stage Researcher (R1) Positions PhD Positions Country France Application Deadline 8 Nov 2025 - 23:59 (Europe/Paris) Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Mar 2026 Is the
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 1 day ago
Website https://jobs.inria.fr/public/classic/en/offres/2025-09541 Requirements Skills/Qualifications Eligible candidates should have a PhD in computer science. Experience in formal methods or in
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particular focus on digital methods and tools. The C²DH's ambition is to venture off the beaten track and find new ways of doing, teaching and presenting contemporary history of Luxembourg and the history
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the Department of Engineering Your profile Education and Scientific Background PhD in Mathematics, Engineering, or a closely related discipline with a focus on modelling, optimization, or data analysis Detailed
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nanoparticles, whose manufacture is generally based on “trial & error” methods. Thus, the aim of TOSCaNA is to develop an experimental approach and a CFD formalism for predicting the size and morphology of metal
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training an autonomous agent to ‘learn’ a control strategy. This formalism is similar to that of optimal control, with the difference that the agent does not have an explicit model of the dynamics