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for reproducible, efficient and scalable training and inference on parallel, distributed and GPU-accelerated computing systems Benchmark the developed approaches against established methods, assessing
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embedded FPGA-based intelligence near seismic sensor arrays, you will explore methods to maximize prediction performance while minimizing data transmission and latency. Your key tasks include: Evaluating
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Your Job The increasing complexity of future power systems, driven by renewable energy integration, power electronics, and distributed energy resources, requires computational methods capable of
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French National Institute for Health Research (INSERM) | Lille, Nord-Pas-de-Calais | France | about 1 month ago
experience, motivation, and potential to contribute to the research programme. Company Founded in 1964, Inserm is a public scientific and technological institute which operates under the joint
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French National Institute for Health Research (INSERM) | Lille, Nord-Pas-de-Calais | France | 4 days ago
Energy Metabolism Employer French National Institute for Health Research (INSERM) Location Lille (Arrondissement), Nord (FR) Salary Salary will be determined according to the candidate’s profile and
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feeds Scaling analog in-memory computing towards large generative AI models H/F 192 / 778 vacancy Vacancy details Position description Category Micro and nano technologies Contract Internship Job title
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systems biology . The successful candidate will join a highly collaborative research environment involving Inria, the University of Lille, Inserm and Lille University Hospital . The position is based at
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two companies. The project has partners from eight different EU countries. All 15 Ph.D. projects are within the overall theme of neuromorphic computing and analog signal processing, targeting
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Your Job The PhD will investigate the relationships between transpiration, effective soil water potential and leaf water potential under contrasting soil and climatic conditions. You will combine
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Your Job Several positions are available in distinct project areas: 1) Associative memory based computing: This project will utilize concepts including Dense Associative Memories and Modern Hopfield