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fermentation–separation processes to enhance efficiency and reduce fuel costs and lifecycle greenhouse gas (GHG) emissions. Research Activities Strain screening: Identify and evaluate microbes for efficient C5
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studentships. Available PhD projects include (detailed project descriptions and supervisor contact details can be found here ): Digital twins with state-of-the-art Gaussian process emulation for decision making
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fluids within the porous structure of sedimentary rocks. These processes are critical for both conventional open-loop geothermal developments and engineered systems, including closed-loop configurations
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programmed in advance. If anything changes, it may fail. This project explores how to build more adaptable systems using vision-language-action (VLA ) models. These combine computer vision (to see), natural
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explore key physical processes governing CO2 plume migration, trapping mechanisms, and fluid–rock interaction under realistic subsurface conditions. The goal is to generate insights that improve the safety
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have the opportunity to develop their computational modelling capabilities in this project, alongside learning new skills such as testing on biological tissues and medical image processing
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-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms, using signal processing/machine learning techniques, to realise all-weather perception in
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yield and productivity. Robust yeast and bacterial strains will be studied alongside continuous, integrated fermentation–separation processes to enhance efficiency and reduce fuel costs and lifecycle
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systems using vision-language-action (VLA ) models. These combine computer vision (to see), natural language understanding (to interpret instructions), and action generation (to respond), enabling robots
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. Using cutting-edge numerical methods and high-resolution simulations, you will explore key physical processes governing CO2 plume migration, trapping mechanisms, and fluid–rock interaction under realistic