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/recruitment/2-year-postdoctoral-p… ** Project ** Computational and high field MRI characterization of learning and decision-making ** Supervisor and contact ** Dr Florent MEYNIEL https://www.unicog.org/lab
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
., "Continual learning for VLMs: A survey and taxonomy beyond forgetting," 2025. 3. Y. Xu, Y. Ban, G. Delorme, C. Gan, D. Rus, and X. Alameda-Pineda, "Transcenter: Transformers with dense representations
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to the international BIDS standard, and BIDSForge for reproducible processing and analysis workflows. The team’s open-source developments are available at: https://github.com/GIN-iEEG . The Research Engineer will also
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in privacy preserving machine learning (ML) within the SSF-ML-DH project, under the supervision of Olivier Cappé (CNRS, DI ENS) and Jamal Atif (Ecole Polytechnique, CMAP). Funding is available for two
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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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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
/hal-04213978 Pierre Cesar, Sofya Dymchenko, Abhishek Purandare, Bruno Raffin. *Learning Where to Simulate: Generative Active Sampling for Online PDE Surrogate Training*. 2026. https://inria.hal.science
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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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platforms and 1,600 partner companies. For more information: https://www.imt-mines-ales.fr You will be joining CERIS, which is home to two research units: the SyCoIA (Complex Systems and Artificial
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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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Potentials (MLIP), machine learning (ML) predictive models and AI tools. Activities : Computer science implying ML and AI tools applied to material science Where to apply Website https://umontpellier.nous