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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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                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 
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                electronics, embedded programming, signal processing, vibration measurement and analysis, maintenance engineering, and electro-mechanical engineering. Funding This is a self-funded PhD. Find out more about fees 
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                This PhD opportunity at Cranfield University invites candidates to explore the integration of AI into certification and lifecycle monitoring processes for safety-critical systems. The project delves 
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                Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded UK Students Prof R Dwyer-Joyce Application Deadline: 30 September 2025 Details Novel Sealing for High-Pressure H2 and Low-Carbon 
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                repair and maintenance of gas turbine engines. Applicants are invited to undertake a fully funded three-year PhD programme in partnership with Rolls-Royce to address key challenges in soft robotics 
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                – United Kingdom PhD programme: Harper Adams University PhD programme Fixed term until 30 September 2028 Research project description Agricultural robots and Artificial Intelligence (AI) technologies could soon be 
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                -suited. By the end of the PhD, the candidate will have gained strong skills in experimental mechanics, test management, materials characterization, and numerical modeling, particularly finite element 
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                EPSRC iCASE PhD studentship with SLB - Computational modelling of advanced geothermal systems School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded UK Students