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to computational models. The group has a leading role in European within the fields of unconventional computing, our Comet initiative , and Computer Architecture, our CAL initiative . The position will be part of
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who have seen a vast number of images from the CoCo-database (https://cocodataset.org ); and apply and interpret the architecture to local field potential data recorded in humans who have seen movies
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requirements at the energy edge. Further, you will incorporate compliance-by-design AI architectures and models and validate our solutions across key energy use cases such as energy market optimization (demand
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environment in which you will collaborate with researchers working across nuclear engineering, naval architecture, electrical power systems, and maritime operations. The project is carried out in close
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of AI/ML software libraries for non-conventional hardware architectures Physics-informed ML surrogates for efficient simulation ML-supported optimization of HPC software Jarli & Jordan/ UiO via Unsplash
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-efficiency requirements at the energy edge. Further, you will incorporate compliance-by-design AI architectures and models and validate our solutions across key energy use cases such as energy market
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network and computing resources to compensate for the gap between physical latency limits and human perceptual tolerances. The work will comprise designing networking and computing architectures
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compliance-by-design AI architectures and models and validate our solutions across key energy use cases such as energy market optimization (demand response, transactive energy peer-to-peer trading, and
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communication in parallel/distributed AI/ML Enhancement of AI/ML with in-network computing & processing Adaptation & optimization of AI/ML software libraries for non-conventional hardware architectures Physics
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physical latency limits and human perceptual tolerances. The work will comprise designing networking and computing architectures that integrate prediction and control algorithms, optimizing data