18 machine-learning-"https:"-"https:"-"https:" PhD positions at University of Nottingham
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a mixture of computational, analytical and machine learning approaches to model the heat transfer to fuels and their physical and chemical behaviour, including changes in chemistry and physical
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This exciting opportunity is based within the Power Electronics and Machines Control Research Institute of the Faculty of Engineering at the University of Nottingham which conducts cutting edge
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and conduct laboratory experiments to assess graphite smoulderability, develop physics-based models to predict scalability, and perform techno‑economic analyses and life‑cycle assessments using machine
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into the sample of interest. Recently we have been using AI and machine learning to predict the distortion present and significantly speed up this correction process. This PhD project will take the latest in AI
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of powder, blending recycled and virgin powder, as well as repurposing of machining scrap and waste wire as feedstock, building on existing proof of concept work. This largely experimental PhD will provide
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characterisation equipment. This largely experimental PhD will provide transferable materials characterisation skills, including optical and scanning electron microscopy. The successful candidate will also learn
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closed‑loop carbon platform suitable for large‑scale deployment. Person Specification Motivation, creativity, and resourcefulness A mature approach to learning Candidates should have been awarded
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moisture risks, directly affecting children’s health, wellbeing, and learning outcomes. This PhD will develop evidence-based, Passive House–informed retrofit strategies tailored to diverse school typologies