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, complexity, and verification needs. By mapping each component to the most appropriate FM tool based on cost-efficiency and expected reliability gains, we aim to construct validation portfolios: automated
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the understanding of offshore turbulence in spatially varying flows. The focus will be on open channel flow dynamics and controlled experimental studies will be designed and conducted to generate and characterise
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-periodic structures, we can precisely control the interaction of radiation with matter, potentially achieving unprecedented timing resolution (sub-70ps) and significantly enhancing signal detection. This PhD
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respond over time (e.g. changing shape), controlled by the arrangement of differential materials within them. The goal of this project will be to develop responsive 4D-printed biomaterial devices for drug
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region and identify mutations. Develop and optimise bioinformatics tools to detect mutations using positive controls. Apply polygenic risk scores (PRS) to genome-wide SNP data to identify individuals
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-printed functional devices interact with their environment, responding to stimuli (temperature, light, etc.), and “4D-printed” devices respond over time (e.g. changing shape), controlled by the arrangement
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recycle content crush alloys. The main objective of the project is to understand the deformation behaviour of the high recycle content crush alloys and the role of tramp elements in controlling the final
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energy; thereby minimising farming’s environmental impact. AI machine learning offers a new expedient method of developing control systems for tasks that would be difficult to manage using classical
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research. The network's goal is to advance infection control protocols, improve implant safety and reduce healthcare costs associated with IAIs. The role holder will develop and characterise novel
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control. Joining the leading researchers in the Centre for Engineering Research at the University of Hertfordshire, collaborating with our industrial partners and becoming a member of the vibrant doctoral