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Inria, the French national research institute for the digital sciences | Saint-Martin, Midi-Pyrénées | France | 2 days ago
understanding of adaptive optimization algorithms which adapt their hyperparameter (e.g., the step size) based on the data accumulated during the optimization process (e.g., during training in a learning
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Inria, the French national research institute for the digital sciences | Grenoble, Rhône-Alpes | France | 17 days ago
algorithms, participate in the development and maintenance of the PEPit ( https://pepit.readthedocs.io/ ) software package, including adding functionalities related to parallel optimization
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process modelling, simulation, and optimization. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7274-BOUBEL-004/Default.aspx Requirements Research Field Engineering Education Level PhD or
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together: https://uclouvain.be/fr/emploi/politique-personnel.html Post description Within the Louvain School of Management (LSM) and the Louvain Institute of Data Analysis and Modeling in economics and
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Inria, the French national research institute for the digital sciences | Gif-sur-Yvette, Île-de-France | France | 17 days ago
activities Access to vocational training Gratification Selection process Website for additional job details https://jobs.inria.fr/public/classic/en/offres/2026-10564 Work Location(s) Number of offers
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optimization of communications, security, and computation in resource-constrained architectures with an emphasis on semantic and context aware communications. The post concerns the study of semantic
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segregation, interface-related energy losses, and insufficient process reproducibility. Addressing these challenges requires a workflow that connects rapid materials and process exploration with
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/voirproposition.pl?site=toulouse&matricule_prop=76476#version Information about the recruitment process will also be available here: https://doctorat.univ-toulouse.fr/cofund-best . (click on the English
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? No Offer Description Context and Challenges The Binder Jetting additive manufacturing process provides substantial freedom in designing ceramic parts with complex geometries. However, numerous
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neural networks, and physics-informed machine learning in power systems Set up benchmark grids and generate or process suitable simulation data for power-flow, voltage-prediction, or state-estimation