304 cloud-computing-"https:"-"https:"-"https:"-"https:"-"https:"-"St" positions at University of Sheffield
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the center's collaborative projects with industry partners to promote the industrialization of technology. ESSENTIAL QUALIFICATIONS/EXPERIENCES A Ph.D. (obtained or soon to be obtained) in Computer
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Exciting Fully Funded PhD Opportunity: Novel Sealing for High-Pressure H2 and Low-Carbon Storage Technologies - Help Shape the Future of Clean Energy Storage! School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded UK Students Prof R Dwyer-Joyce Application...
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evaporation and flow patterns can disrupt the uniformity of the ink film, and in turn degrade the quality, performance, and value of the film. The PhD research programme will look to find ways to control; (i
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or Computer Science. Specifically, applicants must demonstrate experience in writing tools to address flaky tests and have encountered them in practice, including the implementation of mitigation
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Synthesis of Heteroaromatic Boronic Esters via Annulation Reactions of Ynone Trifluoroborate Salts School of Mathematical and Physical Sciences PhD Research Project Self Funded Prof Joe Harrity Application Deadline: Applications accepted all year round Details About the Project We have recently...
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Overview Our postgraduate research student community plays a central role in the research life of the University. PGR students undertake their own programme of research, supervised by an academic
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Reinforcement Learning from Human and AI Feedback (S3.5-COM-Peng)
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Overview The Head of the Integrated Manufacturing Group (IMG) at the Advanced Manufacturing Research Centre (AMRC) is responsible for leading a team of highly-skilled manufacturing engineers and researchers in the technical fields of Automated Assembly, Robotics, Digital Manufacturing and...
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at the University of Sheffield. The unique properties of particles of light (photons) can enable a host of new technologies, such as quantum computing and networking. However, the realization of these technologies
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Topologically constrained physics-informed machine learning for modelling complex spin textures (S3.5-COM-Ellis) School of Computer Science PhD Research Project Competition Funded Students Worldwide