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research activities. The applicant will have obtained or be close to obtaining a PhD in Mechanical Engineering or Materials Science. Appointment at Research Associate level is dependent on having a PhD
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Project Link: Preclinical Evaluation of Spinal Therapies | Project Opportunities | PhD | University of Leeds Number of Positions: 1 Funding: School of Mechanical Engineering Studentship, in support
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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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the opportunity for the PhD student to lead the development of innovative simulation tools that predict Litz wire behaviour across electrical, thermal, and mechanical domains. Supported by the MTC’s advanced wire
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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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Biomedical Campus. You will join an exciting research programme investigating fundamental mechanisms of ribosome assembly, translational control and how defects in these processes drive cancer development
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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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in a degree, ideally at Masters level, in an Engineering subject, Physics, Mathematics, Computer Science or other quantitative background. Knowledge in fluid mechanics, ocean waves, numerical methods
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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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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