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of the PRCI project entitled LUCAS (Leverage External Data for Enhanced Understanding and Causal Attribution of Anomalies in Water Network Systems). The research activities will be carried out at the Centre de
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researchers from several social sciences and humanities disciplines working on transition policies, and offers regular scientific activities (seminars, study days, a network of academic and institutional
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
stimulating scientific and industrial environment of the highest level, with access to a national network of leading research institutions and industry partners, regular interactions with the broader EDT
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the influence of activation conditions on the formation and properties of polymer networks, and to compare different cross-linking technologies under controlled experimental conditions. Particular attention will
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
the development of agentic artificial intelligence systems. Unlike conventional conversational systems, AI agents can generate action plans, invoke external software tools and APIs, communicate with other agents
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software, analytical platform, chemistry and microbiology laboratories. **Main contacts (CNRS internal and external network):** JH Renault (ICMR), Véronique Eparvier (ICSN), Maria Halabalaki (NPMC, Athens
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this PhD project is part of the REFFRACTEUR European Doctoral Network, the 36-month doctoral programme will be organised as follows: Months 1–9 (9 months): the doctoral candidate will work at SAFRAN's
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the REFFRACTEUR European Doctoral Network. The 36-month doctoral programme will be organised as follows: Months 1–9 (9 months): the doctoral candidate will work primarily at the IMERYS research site in Lyon, France
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 3 months ago
fitted with sensors, we can also access precise physical measurements. Recent work in AI-for-Science has shown that neural-network-based meta-models can also assimilate measurements. Machine learning
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challenge the traditional rodent-centric view of URL development and emphasize the need for alternative experimental models, and a deeper understanding of the gene regulatory networks governing URL cell