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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 21 days ago
core of the project is the exploration of leveraging task-based parallel and distributed programming techniques in the DDF-pipeline software components with the aim to accelerate such processing on high
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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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Your Job Design, fabricate, and characterize advanced FDSOI devices for neuromorphic computing applications Develop and optimize semiconductor fabrication processes in a state-of-the-art cleanroom
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; PyTorch; parallel and GPU computing Applicant Profile The internship is intended for a final-year Master’s student or engineering student specialising in applied mathematics, signal processing or
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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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energy-efficient adaptation on analog AI hardware. Contract duration (months) 4 to 6 Job description Within CEA-Leti’s Laboratory of Memory and Computing Devices in Grenoble, you will work on the
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additional programming languages is an advantage Experience with Linux/UNIX-based scientific computing environments and modern software development practices Experience with parallel computing and high
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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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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