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Field
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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
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for transmission or distribution grids, synchronous generators, large loads, transmission networks, etc. Develop simulation algorithms that enable large-scale simulations. Integrate (or co-simulate) grid component
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vision, graphics and visualization, systems, distributed algorithms, and scientific and biomedical computing. Research in the department is and has been funded by numerous agencies, including the National
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healthcare application needs to analyze sensitive patient data across distributed nodes. Researchers and students can explore privacy-preserving algorithms and technologies like federated learning and zero
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variety of key technologies like Distributed IT Systems, Internet of Things, IoT, Cybersecurity, Data Science, Artificial Intelligence (AI), Blockchain Technologies, Quantum & Photonic Technologies
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. These are your qualifications: Must-haves: • Completed doctoral/PhD studies in Computer Science or a closely related field. • You have experience in matrix algorithms, data compression, parallel computing
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with compiler level languages, accelerated computing (preferably with OpenMP or OpenACC) and distributed computing (MPI). A thorough understanding of the particle-in-cell algorithm, its inherent
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control systems, especially EPICS. Familiarity with synchrotron light science (e.g., ALS) preferred. Experienced in RF technology, magnetics, distributed controls, and algorithm design. Strong academic
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, the post-doctoral fellow will consider designing distributed learning algorithms for streaming manifold-valued data. Experiments will be carried out on urban, coastal, and underwater DAS data. The novelty
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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing