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of laminar/neuropixel probes and electrical microstimulation to study attention and decision making networks in a behaving animal model together with parallel studies in humans. The project is part of a NIMH
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: Rethinking AI for Just and Sustainable Futures programme. CFI is a highly interdisciplinary research centre addressing the challenges and opportunities posed by artificial intelligence (AI). Funded by
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: Rethinking AI for Just and Sustainable Futures programme. CFI is a highly interdisciplinary research centre addressing the challenges and opportunities posed by artificial intelligence (AI). Funded by
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experimental collaborators using different X-ray spectroscopy techniques. About the research project Aviation will in the foreseeable future require liquid fuels. There is currently a strong need to improve and
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-source programming framework SkePU for heterogeneous parallel systems. The work includes participation in the regular project meetings and can also include technical meetings with our industry partners in
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than 30 people, including parallel post-doctoral researchers in four other countries, and led by Prof Ben Baumberg Geiger at King’s. Secondly, it’s located within the Centre for Society and Mental Health
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for the quality of its medical expertise, facilities and teaching. The Neuroscience and the Mental Health Program is one of the leading research programs in the medical school. The key objective is to conduct both
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generally to develop new distributed edge services. The successful candidate is expected to evaluate metrics such as latency, throughput, availability, and resilience in different applications scenarios
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) for a given Tiramisu program, many code optimizations should be applied. Optimizations include vectorization (using hardware vector instructions), parallelization (running loop iterations in parallel
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without changing the code. Our research team at NYUAD (New York University Abu Dhabi) is developing a new programming framework called Tiramisu [1]. Unlike existing frameworks, Tiramisu can perform