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(PPPA) group at the University of Sheffield, in collaboration with other institutions and industrial partners, pursues a wide programme related to these muon applications. This PhD project is
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of power output suffers as a consequence. As a recent review highlighted, “Computational approaches that enable higher-fidelity representations under the rapidly changing behaviour of a controlled wind farm
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the air conditions in underground stations. The proposed research will be carried out with the use of Computational Fluid Dynamics (CFD) to simulate the underground station environment with the possibility
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. Research in the group is a mixture of experimental and computation work. Research tools to be used are likely to include lab and pilot scale experimentation. You will use the state of the art
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Improving Deep Reinforcement Learning through Interactive Human Feedback School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Bei Peng, Dr Robert Loftin Application
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together with a dynamic and friendly team of researchers across two different laboratories including cell biologists, biophysicists and computational experts. This project will give you the opportunity
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Adopter programmes, where appropriate. We are looking for an enthusiastic, motivated graduate in (health) Data Science, Computer Science or related field who is interested in the deployment, user acceptance
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be used to demonstrate the ability to detect both gradual degradation and faults in the machine. Training & Skills You will benefit from a taught programme, giving you a broad understanding of the
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Autonomous Industrial Perception, Monitoring, and Optimisation Using an Agentic Framework with Large Language Models School of Computer Science PhD Research Project Directly Funded Students
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. This PhD project is set within the Fusion Engineering CDT at The University of Sheffield. Students will receive a 3-month training programme in fusion engineering at the start of the course, delivered across