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Field
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. The overall aim of this PhD project is to analyse droplet impact mechanics along with the freezing thermodynamics under high airspeeds to gather important insights into ice adhesion behaviour. The experiments
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synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project
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Cranfield University's tailored researcher training programme – setting you up for a rewarding career in water science and environmental technology. Per- and polyfluoroalkyl substances (PFAS), also known as
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This self-funded PhD research project aims to develop smart sensors based on low-frequency resonance accelerometers for condition monitoring of ultra-speed bearings. The developed smart sensors will
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the growing demand for sustainable AI-enabled systems, this PhD brings together low-power computing, energy-aware design, and thermal optimisation. You’ll work with advanced profiling tools, prototype long-life
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
) in a relevant discipline such as aerospace engineering, mechanical engineering, electrical engineering, computer science, applied mathematics, or a closely related field. Experience or interest in
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supervisors spans five departments at University of Nottingham including Architecture and Built Environment, Electrical and Electronic Engineering, Mathematics, Physics and Social Sciences. The PhD programme
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Research Studentship in ‘Deformation and fracture of TRISO fuel particles’ 3.5-year DPhil studentship Supervisor: Prof Dong Liu, Prof Emilio Martinez-Paneda About the Project The proposed PhD
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This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves