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manner. You will be joining the HyPT center to support the work programme on policies, economics, and markets. As an engineering scientist with expertise in the modelling and optimisation of energy systems
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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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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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, in collaboration with Rolls-Royce, will develop innovative coatings to safely contain hydrogen in critical aerospace materials through experimental and computational modelling work. You’ll join a
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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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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