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| £20780 + £2500 industry top up (per annum (tax free)) Overview This exciting, fully-funded PhD opportunity invites applications from candidates with a robust foundation in data science, modelling, and
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for understanding natural magmatic processes on earth & other planetary bodies. Neutron diffraction is a powerful technique for studying the atomic scale structure of these materials, but the current technology to
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modelling. This exciting project involves the application of innovative methods such as high-throughput experimentation to expediate the syntheses (and bioanalysis) of life-saving pharmaceuticals
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-frequency Joule losses. Litz wire is one of the most promising solutions due to its exceptional ability to reduce AC losses and boost power density. Today's modelling tools are not yet equipped to fully
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supercritical water systems to generate samples that will help optimise a process that will then be scaled into pilot and large scale pilot systems with partners in the consortium. Aim This project will focus
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, combustion, and process optimisation. The project is focussed on the development of novel interface capturing Computational Fluid Dynamics methods for simulating boiling in Nuclear Thermal Hydraulics
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rely on unsustainable materials and on carbon-intensive manufacturing processes. This is posing major environmental and ethical challenges. The project will motivate the PhD student to develop next
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of deep learning models, especially when new training experiences are corrupted. The framework will be validated in robotic control scenarios during EV battery assembly, under process variations such as
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, compositional practice, and conceptions of Western Classical music in the Caribbean were shaped by economic and cultural imperialism, by colonial structures of power and knowledge, exploitative practices, and
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, the student will be able to utilise cutting edge equipment to study single atom catalysts anchored on defective graphene substrates. Catalysis is a key industrial process that underpins not only the supply