114 machine-learning "https:" "https:" "https:" "https:" "https:" positions in France
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been revolutionized in recent years by machine learned interatomic potentials (MLIP), and questions that were impossible to tackle five years ago can now be addressed. The state-of-the-art approach
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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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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Sophia Antipolis, Provence Alpes Cote d Azur | France | about 1 month ago
problèmes complexes. -Bonnes compétences en gestion du temps et en communication.- Background in probability, statistics, machine learning, and wireless communications. - Interest in causal inference
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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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. The PhD will focus on two complementary approaches: 1) Enhancing CDI with machine learning: improve this technique using convolutional neural networks (CNNs) trained on simulated data, enabling faster and
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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 1 month ago
computational mechanics and scientific machine learning. The successful candidate will work on the design of hybrid, physics-informed modeling and identification frameworks for complex dissipative material
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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 1 month ago
of the ERC Consolidator project AUTOMATIX (see details below), we are seeking a PhD candidate to develop machine learning approaches for constitutive modeling. Context With the advent of machine-learning (ML
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anomaly detection using advanced and optimized methods. • Literature review (image processing, deep learning, vision-language models, diffusion models, etc.). • Generative AI for creating reliable models
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a