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Laboratoire de Chimie Théorique, Sorbonne Université & CNRS | Paris 15, le de France | France | 4 days ago
of renormalization in a finite basis; • Software implementation and development, integrating the newly developed methods into quan- tum chemistry codes. Working Environment: The PhD student will be hosted
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: LRGP (University of Lorraine – CNRS), LPSM (Sorbonne University – CNRS), the utility EDF R&D, and the process simulation software provider Fives ProSim. PHD DESCRIPTION: The PhD is part of Work Package 3
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/representation. Software development: ability to design and implement both exact (e.g., decomposition methods) and approximate solution approaches for large-scale optimization problems. A good command of English
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. Research within LIG is organized into 5 focus areas: Intelligent Systems for Bridging Data, Knowledge and Humans, Software and Information System Engineering, Formal Methods, Models, and Languages
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translational medicine, improving diagnostics and healthcare solutions. For more information, please visit our page . Your role We are looking for a highly motivated PhD candidate interested in AI-based methods
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or other large-scale biological data), using statistical methods, pathway/network analysis or machine learning. The candidate will conduct integrative analyses of biomedical datasets, focusing on single-cell
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the formal and functional properties of gestures and their relationship to discourse. - Support for computational modeling: o Contributing to the gesture–speech modeling carried out by Loria, based
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ICT Services & Applications. Your role The PhD position is part of the CART-4D project, a "Made in Luxembourg" collaboration between the University of Luxembourg and ARSPECTRA . The doctoral candidate
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revisited and new methods of cooperation with UTC's engineering departments developed. Teaching Depending on his/her skills and experience, he/she will be expected to contribute to existing teaching units
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engineering; Formal methods, models, and languages; Interactive and cognitive systems; Distributed systems, parallel computing, and networks. The successful candidate will work closely with teams specializing