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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
placement with Rolls-Royce. The research focuses on AI-driven digital twins, using large language models and knowledge graphs for predictive maintenance in aerospace systems. Aerospace systems generate vast
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renowned researchers operating at the cutting edge of their fields. Interdisciplinary engagement: Join collaborative research communities across LSBU’s three colleges—including Health & Life Sciences
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failure due to high-cycle fatigue, reducing the efficiency and safety of the gas-turbine engines. The development of robust damper devices that reduce the vibration levels is of paramount importance
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3 years. The studentship is fully funded for 3 years. The pan-University Graduate School offers an integrated training programme to the postgraduate community within a single centre, serving to
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. Your Role: As our PhD student, you’ll be at the forefront of developing smarter solutions, working in partnership with UK Health Security Agency (UKHSA). You'll use anthropogenic approaches and cutting
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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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(AI)-driven speech and voice analysis present transformative opportunities to enhance emergency call triaging. For instance, identifying specific audio features, such as laboured breathing or vocal
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PhD students, the Centre for Sustainable Cyber Security (CS2) has been conducting pioneering research across several areas of cyber security, from trustworthy IoT, and XR cyber security to certified
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bioinformatic tools and focused on clear interpretation and communication of this data. This project is part of an exciting new Doctoral Training Programme in Microbial Genomics for Health Protection in
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initial cycling, which affects safety, longevity, and overall performance. The “RePatina” project will reconstruct and engineer the SEI layer using a combination of operando diagnostics, surface chemistry