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different dyadic motor coordination tasks. A range of neurophysiological measures (EEG, ECG and fNIRS) as well as behavioural measures will be recorded simultaneously from both partners. Machine-learning
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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
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language processing that address concrete problems and are both theoretically rigorous and interpretable. The PhD is funded by the ERC CoG PANDORA (Deep Multimodal Learning for Mining and Generation of Arguments
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, or computer science. Core competencies: solid background in quantum many-body physics strong programming skills (Python required, Rust a plus) experience with tensor networks, variational Monte-Carlo, machine learning
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 28 days ago
learning, privacy, security and distributed systems. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2026-10411 Requirements Skills/Qualifications We are looking for a candidate with
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 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
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 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
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, GC-MS/MS, and advanced NMR approaches. - **Activity 4:** Multivariate statistics and machine learning to identify microbial and chemical biomarkers of resilience and reveal the interactions linking
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, or supervised/unsupervised learning depending on the available data) using spatial analysis and geographic machine learning tools (e.g., scikit-learn, PyTorch/TF + GeoPandas/Shapely) - Implementing a semantic
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 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