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Field
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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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collection methods for external data (e.g. web scraping) to collect data for use in modelling and analysis. Develop analytic plans, engineer supporting algorithms, write new functions or applications in
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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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for the position of assistant professor in the project NCN MAESTRO "Challenging problems in partial differential equations inspired by cutting-edge algorithms in statistics and machine learning
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frameworks, as they impose minimal, if any, assumptions about the underlying data distribution, making them more effective for detecting a wide range of changes. The CPD algorithms will be designed
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distribution can predict both single AZ and whole synapse function at the neuromuscular junction (NMJ). Adapt and convert an existing, experimentally validated MCell simulation of mammalian NMJ AZs into Python
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individually, make a real difference. The role To research and develop software modules, tools and API for a project that aims to create a secure decentralised data marketplace based on distributed ledger
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support to faculty and administrative staff. Continuously monitors OIRDS applications and program scripts to distribute workloads efficiently across servers, ensuring optimal system performance. Implements
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and its implementation in distributed systems. Main responsibilities: Research, develop, and optimise machine learning algorithms, including deep learning, for AV control and coordination. Apply multi
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theoretical physics, whose responsibilities relate to distributed systems and the GPU optimization of AI algorithms. We expect the team to grow in size considerably over the next few years, and are looking