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Field
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intense search is performed to find a correct solution of what is measured. By combining state-of-the-art laser ultrasonic imaging techniques with advanced artificial intelligence, the aim of this project
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The rapid development of Quantum Technologies 2.0 over the last two decades - especially in quantum communication, simulation and computation - has pushed this field into the mainstream of technological innovation, with the expectation of major economic impacts. While universal quantum computing...
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We are excited to offer a fully funded PhD position at the intersection of big data, artificial intelligence, and urban mobility. The rapid development of big data analytics, along with advances in
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Fully funded Ph.D. opportunity in Aerospace AI. Sponsored by EPSRC and BAE Systems covering tuition, fees and a bursary of up to £19,569 (tax free). Combinatory Artificial Intelligence (also known
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the world-transforming field of Artificial Intelligence, commencing 1st October 2024. The studentships will have a duration of 48 months, with an annual stipend at the UKRI rate (currently £19,237
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students for fully-funded PhD studentships to carry out multidisciplinary research in the world-transforming field of Artificial Intelligence, commencing 1st October 2024. The studentships will have a
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) dynamically manage renewable energy technologies outputs and discovery & optimize new designs of future zero-carbon multi-energy systems. This PhD project will cooperate with national and international projects
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structures. The PhD student will be hosted at the Artificial Intelligence Research Centre (CitAI) and work in collaboration with colleagues at the Department of Psychology. The project will examine how
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Predicting the dynamic response of materials and structures to high energy ballistic impacts is a fundamental component of the development and design of fit-for-purpose armour and protection systems. Understanding the ballistic response of protection systems conventionally involves impacting...
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the theme of: Artificial intelligence and data science in MLTCs Our research theme embraces the exceptional capacity of Machine Learning (ML) to identify patterns in vast collections of electronic health