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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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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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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
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Ecole supérieure de physique et de chimie industrielles de la ville de Paris | Paris 15, le de France | France | about 1 month ago
various experiments. In one of the experiment, it is necessary to test insulating samples by recording all events appearing before the breakdown voltage. These data will be then analyzed with artificial
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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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(C2MA), the environment and risks (CREER), artificial intelligence and industrial and digital engineering (CERIS). It has 12 technology platforms and 1,600 partner companies. The person recruited will be
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Foundation. The position will suit researchers interested in developing state-of-the-art methods in economics to develop our understanding of current and future environmental impacts of artificial intelligence