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materials with the high performance of liquid systems. Through innovative ultraviolet photopolymerisation, you will synthesise and optimise eco-friendly GPEs using varying polymer blends, solvents, and
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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the PhD student in high-performance computing, computer programming, applied mathematics, fluid mechanics, mathematical modelling and data analysis for large datasets -of the order of 100 Terabytes
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performance will be assessed using finite element analysis and experimental work. Additionally, life cycle assessment will be performed to quantify environmental and economic impacts. This project is intended
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to perform data work with high accuracy and attention to detail We offer an occupational pension scheme, generous annual leave, hybrid working and excellent training and development opportunities. For further
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plants. These advantages include being more compact, lower costs, using single-phase fluid rather than two-phase fluid used in steam turbines, higher cycle efficiency when using low temperature heat
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contemporary high-resolution next-generation sequencing and array-based genomic and epigenomic datasets across large cohorts of human tumours and experimental models, alongside complex drug screening, efficacy
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improves the performance of ROMs, making them more applicable to real-time structural health monitoring, vibration analysis, and control design. This research offers real-world impact across several
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diagnostic capabilities. The skills and knowledge gained will be transferable to other applications requiring high-performance radiation detection and advanced material interfaces. Through
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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