43 web-programmer-developer-university-of-liverpool PhD positions at Cranfield University
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the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
Fully funded PhD at Cranfield University, supported by the EPSRC DTP and Rolls-Royce. This 3-year project covers tuition fees, a tax-free stipend, and funding for training, conferences, and a
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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We are pleased to announce PhD studentship project in “Advanced Composites Development for Hyper-velocity Impact Protection of Space Satellites Structures”. This is an exciting PhD research
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years EligibilityUK, EU, Rest of world Reference numberSATM450 About the host University and Through-life Engineering Services (TES) Centre Cranfield is an exclusively postgraduate university that is a
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computational and experimental fluid dynamics in addition to product development. This project falls within the field of fluid dynamics, a discipline central to improving the efficiency of systems that involve
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to identify the material degradation and coatings applications details in extreme environments. A novel techniques/method will be developed with focus on better prediction and more accurate measurement of
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development over the last two decades. This research topic aims to define novel approaches to developing and combining these intelligences, utilizing both 1st and 2nd wave AI approaches, in the context
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This PhD project will focus on developing, evaluating, and demonstrating an intelligent solution of diagnosis and prognosis for rotating machinery to enhance safety, reliability, maintainability and
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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