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methodologies, simulation tools, and work contexts while remaining effective in the face of unforeseen events and scientific challenges. Additional comments NTR Website for additional job details https
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, preferably related to serious games and/or agent-based modeling and simulation Desired experience: 2 to 5 years of professional experience Where to apply Website https://www.aplitrak.com/?adid
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, preferably related to serious games and/or agent-based modeling and simulation Desired experience: 2 to 5 years of professional experience Where to apply Website https://www.aplitrak.com/?adid
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
of Copenhagen (UCPH), alongside Universidad Rey Juan Carlos (URJC, ES), University of Twente (UTWENTE, NL), Copenhagen Academy for Medical Education and Simulation (CAMES, DK), InSimo (FR), AMBU A/S (DK) and
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generation, targeted atomistic simulations, structural descriptor extraction, and predictive models. The work will aim to establish links between local pore geometry, structural disorder, sodium adsorption
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21 Aug 2026 Job Information Organisation/Company CNRS-LMA Department laboratoire de Mécanique et d'Acoustique UPR 7051 Research Field Mathematics » Computational mathematics Engineering » Simulation
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: 25 months, part-time (50%) Location : Université de Caen Normandie, France Main host organisation : NIMH Unit, Inserm-EPHE- Université de Caen NormandieU1077 (https://nimh.unicaen.fr/fr/accueil
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. Where to apply Website https://www.unilim.fr/recrutement-post-doctorant-projet-multimoc-grafic/ Requirements Research FieldPhysics » OpticsEducation LevelPhD or equivalent Skills/Qualifications Strong
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on deep learning coupled with molecular simulations for the investigation of slow variables and transition pathways describing large conformational changes and reactive processes in complex biological
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, validate them through simulations, and contribute to their experimental implementation. The first objective will be to formulate and study local learning rules compatible with the nucleation, propagation and