44 software-verification-computer-science-"DIFFER" PhD positions at Cranfield University
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This exciting fully funded PhD, with an enhanced stipend of £25,726 per annum (with fees covered), will deliver a comprehensive understanding of micropollutant removal in different types of nature
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Resilience (WIRe) , a prestigious collaboration between Cranfield University, the University of Sheffield, and Newcastle University. The WIRe programme offers bespoke training that hones both technical and
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honours degree in materials science, physics, engineering, or a related discipline. The ideal candidate will be self-motivated, with an interest in both computational modelling and practical manufacturing
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for Security Operations Centres (SOCs) while pioneering strategies for quantum-era resilience. This project sits at the intersection of Artificial Intelligence, Cybersecurity, and Explainable Computing. It
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evaluation. Prognostics is an essential part of condition-based maintenance (CBM), described as predicting the remaining useful life (RUL) of a system. It is also a key technology for an integrated vehicle
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with engineering, physics, mathematics, acoustics, fluids, electronics or instrumentation background. Prior experience in computational modelling is beneficial, but not mandatory. Similarly, experience
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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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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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innovation through applied research, bridging academia and industry. Students will have access to state-of-the-art laboratories, hardware/software resources, and design facilities, supporting AI-powered
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. Despite some success stories of the use of ultrasound/AE-based technologies for CM of low-speed bearings, high investment cost for hardware and software is the main bottleneck in adopting these technologies