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Your Job In addition to completing your PhD degree, your primary objective is to establish a real-time processing architecture that improves gravitational wave detection sensitivity. By utilizing embedded FPGA-based intelligence near seismic sensor arrays, you will explore methods to maximize...
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computing, scientific computing, and energy systems Your Profile Excellent university degree (Master’s) in Electrical Engineering, Physics, Applied Mathematics, or a related discipline Strong motivation
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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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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
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Position Description The Physics Department at National Cheng Kung University (NCKU), one of the best institutes in Taiwan, invites applications in all areas of Physics for tenured/tenure-track
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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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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
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Computing Devices at CEA-Leti in Grenoble, you will contribute to the development of Bayesian learning methods suited to resistive memories (ReRAM). You will build on the team’s previous work, which
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requires an unprecedented computing and storage infrastructure. Processing these enormous amounts of data in a future data center, however, consumes significant resources. The fundamental challenge is: How