85 web-developer-university-of-liverpool positions at Cranfield University in United Kingdom
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We invite applications for a self-funded PhD to explore innovative research in the development of human-centred embodied multi-agent systems that able to compensate and augment human capabilities in
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This PhD opportunity at Cranfield University invites candidates to pioneer research in embedding AI into electronic hardware to enhance security and trustworthiness in safety-critical systems
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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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university or in industry with experience in both experimental wind tunnel testing and hypersonic CFD with real gas effects. Funding Sponsored by UK industry at standard CDT studentship rate for 4 years
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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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to develop enhanced NbS strategies that target micropollutant removal and remain compatible with other ecological and environmental benefits. The aims of this project are therefore to 1) benchmark the long
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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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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
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This self-funded PhD opportunity is open to both UK and international students with a strong background or willingness to develop expertise in offshore engineering, human factors, digital twin
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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field