7 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" positions at IFP Energies nouvelles (IFPEN)
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job details https://www.ifpenergiesnouvelles.com/ Work Location(s) Number of offers available1Company/InstituteIFPEN LyonCountryFranceState/ProvinceRhone-AlpesCitySolaizePostal Code69360StreetRond-point
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SAF combustion. Recent advances have demonstrated that machine learning techniques, particularly neural networks, can significantly accelerate chemical kinetics computations. Nevertheless, most of
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-9003 Funding: PEPR SPLEEN AMHYABLE (https://www.pepr-spleen.fr/projet/projet-amhyable/ ) Where to apply E-mail karine.truffin@ifpen.fr Requirements Research FieldEngineering » Mechanical
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Infrastructure? No Offer Description This project is part of the European ERC Synergy project Karst https://erc-karst.eu/ , which aims to develop a predictive flow model for an entire karst network. We will
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Paris PSL Geosciences Center in Fontainebleau) as well as from the proximity to students working on related topics (e.g., machine learning and experimentation using micromodels). The advances enabled by
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Bois PréauGeofield Contact City Rueil-Malmaison Website http://www.ifpenergiesnouvelles.com/ Street 4 avenue de Bois-Préau Postal Code 92852 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn
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difficult to couple with basin simulators. Geochemical metamodels, particularly those based on machine learning, can significantly reduce computation times while maintaining physico-chemical consistency