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into host cells. They play a central role in the spread of antimicrobial resistance and in numerous pathogenic processes. This doctoral project aims to elucidate the molecular mechanisms of substrate
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on fluctuation of fluorescent molecules methods as they don’t need any specific materiel or fluorophore. The super-resolved image reconstruction is formalized in mathematical terms as an inverse problem with
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FieldComputer scienceYears of Research Experience1 - 4 Research FieldMathematicsYears of Research Experience1 - 4 Additional Information Eligibility criteria Skills/knowledge: computer vision, neural networks
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and adapted tools for the processing of signals or images acquired with biomedical sensor networks (cardiology, neurosciences) or in geosciences (seismology and marine ecology), but also in wireless
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to join the AI for Genome Interpretation (AI4GI) group at the IGMM (CNRS, Montpellier) for 18 months. The project is a collaboration between IGMM and IMAG, at the interface of genetics, bioinformatics
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from fossil fuels. Yet, many industrial and transport applications still rely on combustion due to their need for high energy densities and thermal processes. Electrofuels (e-fuels), produced from
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of the work is to advance and automate the use of ptychography on various sample types. In particular : 1) accelerate the reconstruction process using a multislice algorithm 2) allow a 3D reconstruction and 3
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internationally recognized expertise in skeletal tissue reconstruction and imaging, at the crossroads of biology, medicine, and engineering. Our team brings together orthopaedic surgeons, dentists, veterinarians
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work will be organized around the following areas: 1. Bee detection and tracking: Development of computer vision algorithms to identify and track each bee from high-resolution images, while
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since 2009, currently contributing to the analysis and operation of XENONnT. The XENON group at SUBATECH includes 5 permanent researchers (2 from CNRS, 2 from IMT Atlantique, 1 from the University