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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems
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, Psychology, or a related field, to be awarded before March 1st, 2026. Essential skills include an ability to code (e.g., Python, R) and interpret data, knowledge of machine learning and statistics, and a
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combines flow and materials chemistry, characterisation, and reaction optimisation. You will gain skills in synthetic co-ordination chemistry, advanced characterisation techniques, machine learning and
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biodiversity support, cooling, air quality regulation and access to nature. By integrating Earth observation, spatial AI, machine learning and socio-environmental datasets, the project will reveal where blue
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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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Subject area: Drug Discovery, Sustainability, Laboratory Automation, Microfluidics, Machine Learning Overview: This highly interdisciplinary 4-year funded PhD studentship will contribute to cutting
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PhD studentship: Teaching Intelligent Agents to See, Think and Act with Vision and Language Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI
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with, cloud computing and virtualisation technologies Familiarity and hands-on experience with machine learning techniques desirable Desirable to have work experience (through internships or similar) in
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sluggish diffusion kinetics of HEAs make them excellent candidates for resisting oxidation and corrosion in high-temperature steam. Guided by thermodynamic modelling and machine learning, we will identify
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these syndromes occur where and when they do? The student will develop statistical and machine learning models to (i) explain the occurrence of extreme fires and (ii) predict their likelihood under present and