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research colleagues, and to learn about the larger context of my research and the research project. Offer: The aim of this PhD research is to optimize acoustic metasurfaces of finite size using machine
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, integrating machine learning and physiological computational models (patient digital twin) to: 1) combine physiological knowledge and clinical data; 2) improve model interpretability; and 3) minimize
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in the center of Paris. He/She will integrate the MLIA team (Machine Learning and Deep Learning for Information Access) at ISIR (Institut des Systèmes Intelligents et de Robotique). MLIA is
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Université Gustave Eiffel / IFSTTAR - Site de Marne-la-Vallée | Champs sur Marne, le de France | France | 13 days ago
doctoral PHD Country: France Requirements Specific Requirements The candidate must: 1) Have a Master 2 or equivalent in Machine Learning, AI, Applied mathematics, mathematics, transportation engineering
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in Entreprise Blockchain and Artificial Intelligence Trustworthy artificial intelligence (AI) is a multifaceted concept underpinned by three critical pillars: Trustworthy Machine Learning, Trustworthy
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machine learning and data science to make 6G networks "AI-native". You will join a high-performance global team committed to driving continuous improvement and world-class innovation in networking research
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the Nokia Standards AI & Data practice, applying the latest advances in machine learning, logical reasoning and data science to make 6G networks "AI-native". You will join a high-performance global team
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managed through power reserves that are provided by synchronous machines. The significant penetration of DERs, connected to networks by power electronics, tends to reduce the number of synchronous machines
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institute of Mines Saint-Étienne and the Laboratory of Informatics, Modeling and System Optimization (LIMOS, UMR 6158) is opening a PhD position in knowledge representation and machine learning, to work
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machine learning. The choice of the most suitable machine learning technique for such modeling depends on the quantity of data, its quality and the time available to build the model. Hybrid modelling