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third over the past 25 years, which is inferred from sparse soil data and the widespread decline of their avian predators. Recent developments in soil geophones and contact microphones have enabled
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interpretation of the data generated and that’s where this project comes in. You’ll be applying metagenomic techniques to respiratory samples and developing analysis and interpretation approaches that facilitate
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. The project will thus reveal whether bacterial factors are driving the recent increase in CDI rates. This information can be used to develop novel prevention and treatment strategies. This project is part of
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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leverage low-precision accelerators for scientific computing by using a number of tricks, known as "mixed-precision" algorithms. Developing such algorithms is far from trivial. We can look at computational
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This fully-funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA), Cranfield University and Spirent Communications, offers a bursary of £24,000 per annum, covering full
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2025 and funding is available for home students at the current UKRI rate (tax free stipend of £20,780 plus tuition fees). Postgraduate Experience The University actively supports equality, diversity and
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experiments; supporting other group members with data analysis and interpretation from both simulations and experimental data; and use the developed framework to design new materials with optimised performance
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project will develop a rigorous theoretical framework to ensure both coordinated behaviour and safety in interconnected dynamical systems. You will design and analyse a two-layer control architecture
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. By joining this project, you’ll develop solutions vital to these cutting-edge applications. About the Thermofluids Group The Thermofluids Group at the University of Sheffield leads pioneering research