562 cloud-computing-"https:" "https:" "https:" "https:" "https:" "St" PhD positions in United Kingdom
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reports to develop computational models that predict identification reliability. They will learn to design interpretable, legally robust AI systems, including attention-based deep learning models and
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Large-scale wind turbines, specifically
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In this PhD you will help explore a new trajectory for AI research, EVE - everyone virtuoso everyday - to succinctly summarise the drive of the work. That is, we are interested in defining and evaluating a class of AI technology that enable expressive, individual and masterful interactions, like...
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), strong quantitative and computational skills, and experience working directly with a major national infrastructure operator will significantly enhance the student’s career prospects. Graduates from similar
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Exciting Fully Funded PhD: Computational Modelling for High-Pressure, Low-Carbon Storage Technologies. Be a Key Player in Shaping the Future of Clean Energy Storage! School of Mechanical, Aerospace
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not essential How to apply: Interested candidates should submit an expression of interest by sending a CV and supporting statement outlining their skills and interests in this research area to https
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closely with water utilities. The outcomes will support the development of robust decision-support tools to safeguard drinking water quality and safety under a changing climate. The research programme to be
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The School of Computer Science and Electronic Engineering at the University of Essex hosts research in communications, networking, signal processing and optimisation. The post will be based within
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-wzn23), this project will combine advanced synthetic strategies with reactivity studies, detailed physical characterization and computational studies to elucidate electronic structures. Together
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before the deadline. Computational haemodynamic modelling provides a powerful framework for linking blood flow dynamics with cardiovascular disease, using in silico approaches to systematically study flow