345 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Ulster University" Postdoctoral positions in France
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Polytechnique de Paris. The group conducts research at the intersection of statistical learning, machine learning, and data science, with a strong focus on structured data, representation learning, and
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, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology. Achieving
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active materials by making use of artificial molecular machines. SPRING will establish innovative concepts to elaborate (i) active (supra)molecular systems, (ii) new synthetic objects to study some
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the creation of high-precision digital twins. Activity 1: Integration of Photometric Stereo in Meshroom - Implement processing nodes for normal field and intrinsic color estimation. - Integrate deep learning
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 2 months ago
the machine learning community as challenging, high-dimensional testbeds. Notably, the recently developed WOFOSTGym simulator \cite{solow2025wofostgym}, bridging crop modeling and RL, received the Outstanding
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Régis de la Bretèche and Cathy Swaenepoel. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7586-REGDUM-001/Candidater.aspx Requirements Research FieldMathematicsEducation LevelPhD
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these autonomy and self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed
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numerical results with observations from scanning and transmission electron microscopy provided by the partners of the ANR project IMP3D (https://anr.fr/Projet-ANR-24-CE08-3737 . - Select a discrete
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Engineering (PHELIQS, https://www.pheliqs.fr/en ), a joint research unit of the French Commission for Atomic Energies and Alternative Energies (CEA), Université Grenoble Alpes and Grenoble INP, is currently
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic