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Field
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
intelligent methods that integrate large language models (LLMs) and knowledge graphs to interpret technical documentation and structure complex engineering knowledge. The goal is to create digital twins
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Location: Addlestone, Surrey KT15 3LS The Veterinary Medicines Directorate (VMD) is an Executive Agency of the Department for Environment, Food and Rural Affairs (Defra). Our aim is to protect
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to offer a three-year PhD studentship commencing in September 2025. The title of the project to be carried out by the student is: Cultural diversity and global music teacher training: Improving teacher
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engines. The variable rotation speeds, complex loading and operating conditions cause significant blade vibrations. These vibrations, if not properly controlled and reduced, can lead to premature blade
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reliability and operational efficiency. Determining the optimal size and location of PSTs within a network is inherently complex due to the nonlinear and dynamic nature of power systems, necessitating the use
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systems to act as an oversight of the AI. This is costly, complex, and time consuming, nullifying the benefits of using an AI approach. This project’s two aims are (1) Establish the best approach
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that support more integrated preventative approaches to complex needs. This interdisciplinary project is ideal for students interested in applied data science, public policy, and improving outcomes
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essential to determine how these models can be made lightweight in terms of computational complexity, memory footprint, and energy consumption for deployment on edge devices or constrained gateways
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volatile international security environment characterised by the return of great power competition, the Freeman Air and Space Institute (FASI), King’s College London, is seeking applications for a fully
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ambitious research team exploring quantum phenomena in large scale and complex systems, from high-temperature Bose-Einstein condensates to trapped solid-state particles in ultra-high vacuum. We combine