500 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at CNRS in France
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support machine learning applications for analyzing electron microscopy images of nanoalloys. Model interactions between nanoalloys and carbon substrates to reflect experimental conditions, incorporating
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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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, 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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symplectic geometry: Baptiste Chantraine, Vincent Colin, Fabio Gironella, Stephane Guillermou, François Laudenbach, Rémi Leclercq. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR6629-FABGIR
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The expert will participate in the necessary methodological developments and analyses of airborne data recorded by the IAGOS research infrastructure (https://www.iagos.org ) and from other networks, to provide
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their spatial patterns in varying environmental conditions. The successful candidate will integrate to the research unit « Microbial Oceanography - LOMIC : http://lomic.obs-banyuls.fr » in Banyuls sur mer, and
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, Applications of Deep Learning in Electromagnetics: Teaching Maxwell's equations to machines. Scitech Publishing, 2023. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR6164-DAVGON-024
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the network, as well as with academic and non-academic partners. General information about the CLIMES project is available at: [https://www.climes.se/climesdn/ ](https://www.climes.se/climesdn/ ) All working
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) in Paris. It will be co-supervised by Catherine AMIENS, from the LCC's 'Engineering of Metallic Nanoparticles' team (https://www.lcc-toulouse.fr/ en/engineering-of-metal-nanoparticles-team-l/ ) and
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statistical inference, machine learning and population genetics. The expected outcomes include new computational tools for studying B cell evolution, insights into age dependent immune diversity and the