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argon. The analysis of the ProtoDUNE data will help to validate calibration techniques and particle identification algorithms. The candidate should have a good knowledge of particle physics and experience
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processing, data analysis, data-driven modelling, optimisation and computation algorithms, machine learning models and neural network structures, as well as strong skills and experiences in computational
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Deadline: 31 October 2025 Details This project aims to develop new algorithms for reinforcement learning from human feedback, to effectively solve complex reinforcement learning tasks without a predefined
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, including how to guarantee the properties of stability and constraint satisfaction while probing the system and learning a new model. This project aims to develop novel algorithms for the adaptive distributed
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electromagnetic design. We will explore advanced topologies for mmwave metasurfaces, design novel reconfiguration mechanisms, and develop intelligent algorithms to optimize scattering characteristics in real-time
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decision with multiple data sources. One example is to develop the semi-supervised methods and dynamic system interfacing algorithms to produce an automated and real-time information exchange across
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Universities and Colleges Sport (BUCS) leagues and events. This includes ensuring adherence to deadlines, eligibility criteria, and proactively resolving complex entry issues. Take ownership of the scheduling
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scheduling. Activities will include producing and maintaining clinical staffing allocations, ensuring that all clinical teaching events are appropriately staffed. You will work closely with School and Trust
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delivery of student experience as students progress through their programme journeys, from welcome and transition to graduation. You will set the annual schedule of key activities and lead developments to
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/adaptive algorithms, offline and online data analysis, conducting experimental research, and online evaluation of the developed adaptive strategies with a robotic application. The prospective students can