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pollution, support biodiversity and deliver social value. Yet these trade-offs remain poorly quantified in complex urban landscapes. This PhD will investigate how urban blue networks can be optimised for both
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knowledge co-evolution and addressing complex challenges in a super-intelligent society. This project is situated within the rapidly evolving field of Cyber-Physical-Social Systems (CPSS), which is of
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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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of representative failure models for gear failures causes difficulties in their useful lifetime prediction. Critical operational parameters such as loading, speed and lubrication affect the physics of gear meshing
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drone detection and localisation performance using radar systems. This can be achieved by improving the detection performance of individual sensors and by employing a cooperative network of sensors which
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Join our diverse and inclusive team to transform the future of aviation as part of the UK’s EPSRC Centre for Doctoral Training in Net Zero Aviation. This fully funded (including fees for home UK
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categories for a better capability of managing the uncertainty related to system complexity and data availability to achieve more accurate RUL estimations The student will have the opportunity to work with
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
nature makes them susceptible to complex damage modes like delamination, fibre breakage, and matrix cracking, especially under high-velocity impacts from projectiles or debris. Current assessment
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industrial SBSP experts, the candidate will explore the nonlinear structural dynamics of LSSs to fully understand the complexity of their control. They will use this foundation to explore idealised and