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circuit-level simulation, system modeling, and in-silicon hardware prototyping to evaluate approaches against performance metrics such as energy efficiency, inference accuracy and computational latency
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Enhancement of AI/ML with in-network computing & processing Adaptation & optimization of AI/ML software libraries for non-conventional hardware architectures Physics-informed ML surrogates for efficient
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3 Mar 2026 Job Information Organisation/Company UiT The Arctic University of Norway Department Department of Technology and Safety Research Field Technology » Information technology Computer
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hardware prototyping to evaluate approaches against performance metrics such as energy efficiency, inference accuracy and computational latency. The successful candidate will join the Nanoelectronics
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international preparedness. The position is for a period of three years. The objective of the position is to complete research training to the level of a doctoral degree. Admission to the PhD programme is a
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