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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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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
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of 9 people : 4PhD students, 3 post doc, 1 research engineer and 1 assistant. The team is associated with the Institut Pasteur's Computational Biology Department, UMR3738 and the PRAIRIE Artificial
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and risks (CREER), artificial intelligence and industrial and digital engineering (CERIS). It has 12 technology platforms and 1,600 partner companies. The position is part of the European BEST-CROP
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to work on the use of hyperspectral data to explain and predict soil functions and communities in European mountains. We are looking for a candidate who has a very good command of artificial intelligence
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the fields of Artificial Intelligence (AI) and Earth Observation (EO). It has extensive experience in remote sensing, particularly in radar imaging and its application for measuring surface displacement. It