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Field
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and economy that respect people and their environment. We are looking for our next postdoctoral researcher in computer graphics and machine learning to join the Image, Data and Signal (IDS) department
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, machine learning, explainable artificial intelligence (XAI), digital twins, and integrated data-model approaches. • Study of the frugality of the developed approaches by reducing the requirements
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, the ability to analyze the full dataset collected by the experiment will be severely limited. The L2IT is a leader in developing new track reconstruction algorithms using geometric deep learning methods
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deep learning has led to the emergence of Transformers-type networks whose performance has revolutionized the field. These networks are the basis of next-generation image processing models (such as
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interest in data analysis, modelling, statistics, and machine learning. Experience in spatial data analysis (GIS), scientific programming (Python, R, or equivalent), or artificial intelligence will be
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develop and apply cryo-ET on microalgae from laboratory cultures and field samples. At LPCV, you will contribute to the research themes of the Photosymbiosis team led by Johan Decelle (https
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expected to teach computer science at bachelor’s and master’s level. They are also expected to teach robotics. Additionally, they may contribute to the development of our IT courses. They must be able
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learning French and settling in France (relocation agency). Eligibility criteria Candidates must submit their application packages via this link: https://docs.google.com/forms/d/e
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 3 months ago
-tier machine learning and computer vision venues, actively participating in departmental seminars, and contributing to collaborative projects. Where to apply Website https://jobs.inria.fr/public/classic
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condensate dynamics [6] confirm that programmable multi-soliton architectures are now experimentally accessible. In par- allel, AI methods — reinforcement learning and neural- network-based optimization — have