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is part of the PEPR-DIADEM GREENTEA project 'High-speed generation through machine learning of new thermoelectric sulphide alloys composed of abundant elements'. The generation of electricity from
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Description The overarching mission is to conduct research combining machine learning, data assimilation, and physical modeling to enhance short-term (days/weeks) forecasts of Arctic sea ice conditions. The
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and optimize their properties for neuromorphic computing through combined electrical and MOKE measurements, and train them to achieve artificial intelligence tasks. - Micromagnetic simulations - machine
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… and current call: https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/o… * PhD Offer in Montpellier, South of France - Within the doctoral network EURECA, the LIRMM / CNRS is offering
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, cell biology experiments, biochemistry, metabolic profiling, measurement of metabolic or electric activities via probes or MEA system, and in vitro imaging using confocal microscopy). • Animal experiment
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been revolutionized in recent years by machine learned interatomic potentials (MLIP), and questions that were impossible to tackle five years ago can now be addressed. The state-of-the-art approach
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to conduct his own research projects if the scientific scope is compatible with the ERC ATTRACTE (modulo machine time). This position is funded by the ERC Starting Grant ATTRACTE project (2023-2028, PI: G
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Agriculture: Natural Language Interfaces over Robotic and Analytical Farming Systems In the context of the MSCA JD project GreenFieldData https://www.eu4greenfielddata.eu/ GreenFieldData: IoRT Data Management
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anticipating crises. Current landslide prediction models, based mainly on rainfall thresholds, become ineffective in the presence of snow cover. Snow acts as a temporary reservoir, storing precipitation before