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project will take a comprehensive approach, encompassing the design, manufacturing, and characterisation of metamaterial architectures for advanced radiation detection. The research will involve
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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems
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the project. The objective of the proposed research project will be the development of AI-based digital twin technology for performance diagnostic and prognostic predictions of gas turbine engines. A novel
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development over the last two decades. This research topic aims to define novel approaches to developing and combining these intelligences, utilizing both 1st and 2nd wave AI approaches, in the context
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sanitation industries. Working with our established industry partners, you'll implement your innovations in real operational environments, seeing your research make tangible difference while building
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systems and future telecom solutions. This project aims to design a localisation/positioning framework capable of leveraging signals from terrestrial base stations, non-terrestrial networks (presented by
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. The primary output will be a validated, open-source detection framework demonstrably meeting enterprise performance benchmarks (e.g., latency, accuracy). The research will contribute new knowledge through
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trustworthy operation of navigation systems in complex, GNSS-denied scenarios. The ultimate goal is to provide the navigation research community and industry with tools and methods that ensure continuous, high
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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
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using alternative fuels and/or increasing the efficiency of the gas turbines. Additively manufactured materials, could help in increasing the temperature at which GTs will run, with a consequent increase