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intelligent systems aim to optimize power usage without compromising performance, employing strategies like power-aware computing and thermal-aware optimization. These systems are crucial in extending
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these extreme events across a series of complex flows. This will entail performing high-fidelity simulations of a range of flows exhibiting extreme events, developing hybrid physics-based/machine learning
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, characterization and the development of miniaturized devices. Experience with multivariate analysis, computational methods or statistical techniques is highly desirable. The PhD projects are highly interdisciplinary
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Electrophysical remanufacturing of aerospace gas turbine components for performance restoration and critical material safeguarding This exciting opportunity is based within the Advanced
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are invited for a fully funded Industrial Doctoral Landscape Award in partnership with Siemens Digital Industry Software, focused on advancing the next generation of industrial Computational Fluid Dynamics (CFD
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for manufacturing. • Pioneered metal-free processes Reducing reliance on costly and hazardous precious metal catalysts. • Delivered high-performing biocatalysts Engineered industry-ready enzymes suitable for large
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performance at master’s level focussed on Economics, with the expected completion date of no later than September 2026. A background and an interest in applied economics analysis, environmental and energy
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, and environmental pressures, reducing physiological resilience and performance. Current microbiome therapies, such as faecal microbiota transplantation (FMT), highlight the potential of microbiome
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Research Assistant to investigate digital reading comprehension through large-scale data analysis. This role, funded by the John Fell Fund, sits at the fascinating intersection of computational
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to assess feasibility and optimise performance under uncertain subsurface conditions. Two principal configurations are employed: closed-loop systems, commonly referred to as deep borehole heat exchangers