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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves
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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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access to cutting-edge computational tools and interdisciplinary collaboration. This is a self-funded PhD, open to both UK and international students, offering the opportunity to lead an ambitious project
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to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development
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requirements A minimum of a 2:1 first degree in a relevant discipline/subject area (e.g. aerospace, automotive, mechanical, electrical, chemical, computing, and manufacturing) with a minimum 60% mark in
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supervisor/s within the theme are recognised. This is a 12 month, 100% research programme where you will achieve your MSc degree by developing a desk/laboratory/field based novel research project. Our current
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This PhD project offers a unique opportunity to delve into the complexities of free-market systems and sustainability through a novel ensemble prediction model. With a focus on addressing uncertainty and limited data availability, this research aims to revolutionize decision-making in...
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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 focuses on AI-driven fault diagnosis, predictive analytics, and embedded self-healing mechanisms,...
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defence and security studies, and is lauded for the rigour, originality, international perspective and policy relevance of its doctoral programme. The Centre has delivered short training and long degree