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opportunities, international networking prospects, potential commercialisation routes, and the opportunity to pursue a rewarding career in the specific security sector. These distinctive elements collectively
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network and enhancing their career prospects. From this experience, the student will gain a wide range of transferable skills that will significantly enhance their employability. They will develop strong
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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 of Defence
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help you develop into a dynamic, confident and highly competent researcher with wider transferable skills (communication, project management and leadership) with an international network of colleagues
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abursary of up to £19,237 (tax free) per annum plus fees for up to four years. Cranfield Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and professional study
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of representative failure models for gear failures causes difficulties in their useful lifetime prediction. Critical operational parameters such as loading, speed and lubrication affect the physics of gear meshing
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Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network. This network
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Centre is providing its state of the art academic and research services to industrial clients such as Boeing, BAE Systems, Rolls-Royce, Meggitt, Thales, MOD, Bombardier, QinetiQ, Thales, Network Rail
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of the art academic and research services to industrial clients such as Boeing, BAE Systems, Rolls-Royce, Meggitt, Thales, MOD, Bombardier, QinetiQ, Thales, Network Rail, Schlumberger and Alstom.
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling