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of the infrastructure, design and execution of large‑scale measurement campaigns, and development of data‑driven models for room acoustics and spatial‑audio. The specific research direction will be finalised after
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. In this project, you’ll have the opportunity to be trained and become a proficient user of a range of advanced experimental techniques. For instance, you’ll learn how to use in-situ X-ray Computed
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October 2025. Later start date is possible, please contact Dr Isabella Guido once the deadline passes. You will need to meet the minimum entry requirements for our PhD programme. We are seeking a highly
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of developing a computational model to simulate hydro-sedimentary dynamics and morphology between restored patches to explore conditions favourable for restoration. Validated with data on vegetation cover and
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
placement with Rolls-Royce. The research focuses on AI-driven digital twins, using large language models and knowledge graphs for predictive maintenance in aerospace systems. Aerospace systems generate vast
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(developed by B.J. Evans, O. Hassan and K. Morgan). This solver directly solves the Boltzmann-BGK model equation for the velocity distribution function, which is a fundamental quantity in rarefied gas
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candidates with a background in meteorology, climatology, physics, and any related discipline, and a strong interest in applying advanced physical and computational methods to real-world challenges in the area
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– United Kingdom PhD programme: Harper Adams University PhD programme Fixed term until 30 September 2028 Research project description Agricultural robots and Artificial Intelligence (AI) technologies could soon be
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modelling. This exciting project involves the application of innovative methods such as high-throughput experimentation to expediate the syntheses (and bioanalysis) of life-saving pharmaceuticals
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reduces computational cost and enables large-scale reactor simulations, current porous approaches, based on Reynolds-averaged Navier-Stokes models, rely on empirical correlations and assumptions that may