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Field
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interactions. Machine learning: reinforcement learning, or multi-agent systems. Signal processing: spectrum sensing, localization, or radio environment modelling. Multi-agent systems: distributed intelligence
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outcomes. By mapping these gene distributions and integrating them into a predictive tool, the project seeks to stratify patients as likely responders or non-responders to chemotherapy, enabling personalised
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characteristics might explain these differences? MS is a complex disease, with damage to the brain and nervous system that varies widely between individuals. This PhD project offers an opportunity to investigate
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Project advert Madagascar is a globally important biodiversity hotspot, home to hundreds of endemic species. At juxtaposition with this rich natural heritage is a growing human population and a
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. This project seeks to advance energy autonomy by optimising power conversion, storage, and distribution in such systems, enabling broader adoption in real-world applications. The project aims to develop a PMC
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multiple objectives in real-time. The complexity of coordinating these distributed systems while ensuring stability and optimal performance presents a significant technical barrier that must be overcome
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environments.DutiesThe PhD student will carry out research in the area of cooperative autonomous systems. The successful candidate will explore topics such as: Multi-agent reinforcement learning Distributed control
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, or pro rata for part-time study. Students will be based at the CREWW building on Streatham Campus in Exeter. Flooding is the most common natural disaster, impacting billions worldwide. Natural Flood
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pair distribution function (PDF) data for structure refinement and modelling of heterogeneous catalysts Publication of results in peer-reviewed scientific journals and presentation at conferences Your
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the availability and distribution of shaded pedestrian routes in Reading, with the aim of identifying priority areas for shade provision to support equitable and heat-resilient urban mobility. Green infrastructure