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Starrydata2). The work will include the implementation of machine learning models (neural networks, random forests, SISSO), generative approaches for predicting crystal structures, the use of machine learning
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at laboratory and pilot scale, establishing robust process models, and developing targeted optimization strategies. The most promising enhancements will be assessed for industrial-scale implementation
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 15 hours ago
perks for numerous retail, restaurant and performing arts discounts, savings on local child care centers and special rates on select campus events. UNC-Chapel Hill offers full-time employees a
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of errors between model predictions and post-operative reality This work will be carried out by the Biomécamot team (https://www.timc.fr/BiomecaMot ) at the TIMC laboratory, which is part of the CNRS's
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/H2 flames in porous burners using direct numerical simulations (DNS) to understand NOx formation mechanisms. The research, in collaboration with CEA, will utilize the CFD code CONVERGE, employing
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, testing, and analysis of resilient and sustainable geotechnical systems using centrifuge modeling. The work will bridge advanced experimental testing with complementary numerical simulation to generate
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candidate will lead tasks related to experimental testing and numerical modelling to verify structural performance under representative environmental conditions and establish a design envelope for
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research laboratories. ECL’s research activities are directed to and for the business world through numerous industrial contracts. The Ampère-lab is a joint research unit (CNRS, Ecole Centrale de Lyon, INSA
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éventuellement géomatiqueCandidate with a background in Civil Engineering or Earth or Water Sciences, with skills in: Hydrology and Hydrogeology, numerical modeling, computer programming, and possibly geomatics
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approaches to better translate mechanisms between model organisms and human health. The projects require expertise in handling genome-wide datasets and training people with different skill levels on approaches