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engineering, computer science or a related field. The ideal candidate should have the ability to understand engineering systems and have some experience with machine learning techniques. The candidate should be
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Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel
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testing and computational modelling. You'll become part of a diverse, multidisciplinary team that prioritises equity, diversity, and inclusion, gaining specialist expertise in hydrogen-material interactions
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This is an exciting opportunity for a Self-funded PhD studentship in the Centre for Autonomous and Cyber-Physical Systems associated with the Faculty of Engineering & Applied Sciences at Cranfield
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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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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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the identification of topologies and technologies that can support current and future geared architectures. Within this context applying Model Based Systems Engineering principles for defining requirements and
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-generation secure computing. With rising industry demand for AI-electronics expertise, graduates will be well-positioned for roles in cutting-edge research, technology development, and industrial applications
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Thermal Power Engineering offers a specialist, part-time research programme, leading to the attainment of an MSc qualification. Through independent research, this training aims to enhance your career
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to develop the coagulation process for phosphorus removal from wastewater. This is an experimental program that will explore how the type of phosphorus species and water characteristics influence