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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 26 days ago
friendly and stimulating environment that gathers Professors, Researchers, PhD and Master students all leading research on High-Performance Computing. The city of Grenoble is a student-friendly city
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Université de Bordeaux / University of Bordeaux | Villenave d Ornon, Aquitaine | France | 21 days ago
genomic diversity and genetic load from available genomic data for various woody species. For this, you will use the available pipelines from phase 1 of the project and apply machine learning-based methods
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financement Where to apply Website https://www.abg.asso.fr/fr/candidatOffres/show/id_offre/133293 Requirements Specific Requirements Etudiant(e) titulaire d'un Master II en Statistique / Machine Learning
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of Python programming and a deep learning framework, preferably PyTorch. Solid knowledge of image processing, inverse problems, and machine learning. Significant research experience, demonstrated by quality
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materials science, - Machine learning force fields / data-driven techniques for chemistry or materials science Specific Requirements This position involves a significant amount of numerical code development
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of massive galaxies from the primordial Universe to z~2. This project combines a unique JWST dataset with state-of-the art hydrodynamical simulations and machine learning techniques to understand the origins
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project combines techniques from machine learning, natural language processing (NLP), and knowledge representation to support legal scholarship and decision-making. The position entails close academic
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Contexte Les Machine Learning Operations (MLOps) sont devenues
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, Communication, Optimization • SyRI: Robotic Systems in Interaction The PhD student will join the CID team, whose research focuses on Artificial Intelligence, including statistical learning, uncertainty management
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surfaces. Consequently, it is essential to develop mobile measurement instruments and acquire comprehensive datasets to validate and enhance the models. This PhD thesis project, a collaboration between COLAS