-
Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 3 days ago
gross salary / month Selection process Applications must be submitted online on the Inria website. Website for additional job details https://jobs.inria.fr/public/classic/en/offres/2026-10447 Work
-
Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
-offs. Collaborate with researchers from Inria Lyon, Inria Lille and CNRS/LIRIS Lyon. Disseminate research findings through peer-reviewed publications and presentations at leading venues in machine
-
the ERC CoG PANDORA (Deep Multimodal Learning for Mining and Generation of Arguments). Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR7271-SERVIL-002/Default.aspx Requirements Research
-
Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
., Revenko, A., Teije, A. T., & Harmelen, F. V. (2023). Combining Machine Learning and Semantic Web: A Systematic Mapping Study. https://doi.org/10.1145/3586163 [2] Benoît Combemale, Pascale Vicat-Blanc
-
develop a new generation of hybrid models combining large-scale machine learning with physical knowledge to represent interactions between mobile robots and their environment. The research will address
-
Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 3 months ago
(or surrogate models) are approximations of classical numerical solvers with a very low computational cost. They form the core of a digital twin. Using machine learning techniques to build these meta-models
-
Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 3 months ago
into resources that can be used for machine learning. The PhD will therefore investigate multimodal approaches that connect visual sign-language information with textual representations under low-resource