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will be jointly embedded and interact with PhD students and research engineers of the Interdisciplinary Institute for Artificial Intelligence (3iA) TechPool, and operates in the context of international
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chemistry, biomass recovery, the circular economy and advanced materials. Combining experimental approaches and artificial intelligence-assisted theoretical chemistry tools, E2P2L stands out for its close
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including genomic experts, immunologists, pathologists, artificial intelligence specialists, and clinician-scientists. The CRC provides access to state-of-the-art sequencing platforms, digital pathology
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authentic data and the use of artificial intelligence techniques, with the long-term objective of developing automatic recognition and generation systems to animate avatars. The linguistic component, led by
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validated at CPPM. In parallel, the candidate will improve data reconstruction algorithms by using artificial intelligence techniques (e.g. neural networks), to optimize the separation between signal and
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on the development of advanced artificial intelligence and machine learning methods for genome interpretation, with a particular emphasis on modeling the relationship between genetic variation and phenotypic outcomes
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civil engineering (C2MA), the environment and risks (CREER), and artificial intelligence and industrial and digital engineering (CERIS). It has 12 technology platforms and 1,600 partner companies
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aging tests and electrical measurements to assess component reliability. -Ability to analyze and interpret experimental data (physical signatures, correlations with reliability). -Use of artificial
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and optimize their properties for neuromorphic computing through combined electrical and MOKE measurements, and train them to achieve artificial intelligence tasks. - Micromagnetic simulations - machine
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environments (Gazebo, Unreal Engine, or Unity). You have experience in artificial intelligence (Deep Learning, PyTorch) or embedded systems (ROS2, FPGA/VHDL design). You are curious, show scientific rigor and