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Field
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difficult for industry to predict and control product performance. This PhD project will tackle that challenge by applying advanced polymer characterisation techniques to better understand and quantify
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randomised controlled trial (RCT) using a waiting list design. Fifty school pupils aged approximately 11 to 18 with non-anorexic eating disorders will be recruited from schools in the Midlands. Participants
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and controlling defects and lay the foundation for a thermal physics-based approach to process qualification. Additive manufacturing (AM) is a rapidly evolving technology that continues to drive
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apparatus equipped with thermocouples and thermal imaging to simulate realistic runaway events. Top-performing coatings will be validated in situ on live EV cells under controlled runaway conditions. Dr
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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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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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-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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-fast, low-energy optical interconnects in collaboration with Microsoft and two Finnish SMEs. The project focuses on development new optomechanical control methods for macroscopic quantum states of light
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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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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