709 computer-programmer-"https:"-"UCL" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" positions at University of Sheffield
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at l.pasquinalemonche@sheffield.ac.uk Next steps in the recruitment process It is anticipated that the selection process will take place in the weeks following the closing date. We plan to let candidates know
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the recruitment process you can contact Rebecca Swift. Our vision and strategic plan We are the University of Sheffield. This is our vision: sheffield.ac.uk/vision (opens in new window). We are a Disability
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that underpin segregation and performance degradation. The project will be a combination of analytical theory and computational modelling. The successful applicant will be embedded in both the theory group
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process It is anticipated that the selection process will take place the week of 19th January. This will consist of an interview with members of the team. We plan to let candidates know if they have
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is on mathematics and computation. At the heart of the project are value-based decision problems. Here, an agent receives noisy information about the value of several possible options. The agent must
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Model Based Design and Flight Testing of a Vertical Take-Off Vertical Landing Rocket (C3.5-MAC-John)
guidance algorithms [1] for the hopper. These algorithms will run in real-time on a high-performance, secondary flight computer. One of the project’s novel contributions lies in the creation of a fully
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AI4Ed: Multi-Agent Systems for Collaborative Human–AI Writing and Feedback (S3.5-COM-Yuan) School of Computer Science PhD Research Project Competition Funded Students Worldwide Dr Zheng Yuan, Dr
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Speech Technology for Longitudinal Monitoring of Ataxia Progression (C3.5-COM-Ma) School of Computer Science PhD Research Project Competition Funded Students Worldwide Dr Ning Ma, Prof Marios
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Using Generative AI to create design fictions for responsible technology innovation (C3.5-COM-Law) School of Computer Science PhD Research Project Competition Funded Students Worldwide Dr James Law
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Bridging Causality and Forecasting in Space Weather: A Transparent Complex Systems Modelling and Interpretable Machine Learning Framework