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are recruiting a motivated PhD candidate to undertake an exciting project within the EPSRC Energy Transfer Technologies Doctoral Training Hub. As a student of the Hub, you will receive an enhanced stipend
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A funded PhD studentship is available within the Autonomous and Cyber Physical Systems Centre at Cranfield University, Bedfordshire, UK. As aerospace platforms go through their service life, gradual
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This PhD studentship covers fees and stipend for a home (UK) student to investigate how urban blue networks can be optimised to enhance ecological resilience and community wellbeing. The project
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and manufacturing methods. The Centre's contributions to industry are demonstrated through its extensive MSc and PhD research initiatives and its ongoing technology development programs in large-scale
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This PhD project will focus on developing, evaluating, and demonstrating a framework of novel hybrid prognostics solution for selected system use case (e.g. clogging filter, linear actuator, lithium
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This PhD opportunity at Cranfield University invites ambitious candidates to explore the frontier of energy-efficient intelligent systems by embedding AI into low-power, long-life hardware platforms
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The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics. Lack of representative failure models for gear failures causes difficulties in their useful lifetime...
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The research in this doctoral opportunity will investigate the relationship between material elastic and thermal properties by using high resolution digital imaging under dynamic loads. Digital image correlation is an effective tool to characterize material properties. The analysis of the images...
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This exciting fully funded PhD, with an enhanced stipend of £25,726 pa, is sponsored by Anglian Water, Thames Water, Yorkshire Water, Northumbrian Water and EPSRC. The research will address
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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