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Field
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) project aims to develop very high-power batteries (full charges or discharges in a few minutes), as well as the models and control strategies that allow their safe operation. Twelve laboratories in Germany
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observations of material evolution during ion interactions remain largely unexplored. Such knowledge is crucial to understand transient processes and defect dynamics, in order to design next-generation materials
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7 Jul 2026 Job Information Organisation/Company Grenoble INP - Institute of Engineering Department Engineering Research Field Engineering » Computer engineering Researcher Profile Other Profession
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the functional links between transcription factor condensate formation and autophagy, and the involvement of these processes in the temporal interpretation of auxin information and the control of organogenesis
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- Study of stability under operation - Development of kinetic models - Reactor modeling The work will be carried out at the ICPEES (Institut de chimie et Procéder pour l'Energie, l'Environnement et la Santé
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Postdoc (f/m/d) at Rossendorf Beamline at the ESRF / Completed PhD in Physics, Chemistry, Materia...
Helmholtz Association of German Research Centres | Tremblay en France, le de France | France | 2 months agofrom nuclear and industrial waste in collaboration with six European partners (www.malar-project.eu). Your tasks # Providing support during user operation at the XES station (dedicated to high-energy
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description SIMaP (Science and Engineering of Materials and Processes – UMR 5266), a
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28 Jul 2026 Job Information Organisation/Company IMT Mines Ales Department Human Ressources Department Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1
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hypothesis is that seismicity serves as an observable proxy for the coupled processes linking deformation, permeability evolution, fluid circulation, and hydrogen generation. The strategy consists
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deep learning has led to the emergence of Transformers-type networks whose performance has revolutionized the field. These networks are the basis of next-generation image processing models (such as