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Inria, the French national research institute for the digital sciences | Grenoble, Rhone Alpes | France | 13 days ago
the Thoth project team (https://thoth.inrialpes.fr/ ) within the Inria Centre at Université Grenoble Alpes (https://www.inria.fr/en/inria-center-universite-grenoble-alpes ) to work under the supervision
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practice of machine learning would be an asset. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR8188-MARHEC-007/Default.aspx Work Location(s) Number of offers available2Company
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required. •Experience with deep-learning techniques and libraries welcome. •Past experience in neutrino oscillation and/or LAr TPC experiment welcome. Website for additional job details https
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 9 days ago
: tyrex.inria.fr Relational learning has recently gained renewed momentum through the development of end-to-end deep learning approaches over relational databases. In this setting, relational tables are typically
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be responsible for designing and implementing physics-informed machine learning strategies for identifying constitutive laws in granular media. This includes the development of thermodynamically
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investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable states, attractors
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 11 days ago
. In Proceedings of the Fourth Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC 2026. https://arxiv.org/abs/2602.13905 Clérice, T., Pinche, A., Vlachou-Efstathiou
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learning, epigenomic data, and mechanistic modelling. The mission is to contribute to the development of predictive models of the replication initiation probability landscape (IPLS) from limited experimental
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unsupervised learning. These methods will be based on new classes of partial differential equations on graphs and new graph neural network models based on diffusion processes. The developed algorithms will be
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scientific articles, presenting research results on conferences, and communicating with collaborators The Institute of Electronic, Microelectronic and Nanotechnology (UMR CNRS 8520 – https://www.iemn.fr/en