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Application deadline: All year round Research theme: Computational Chemistry, Material Science No. of positions: 1 Eligibility: UK students This 3.5-year project is fully funded by industry and home
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orbital parameter extraction using image processing techniques. The ideal candidate should have a strong background in physics, engineering or a related field, as well as experience working with programming
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Discipline: Engineering & Technology, Civil Engineering Qualification: Doctor of Philosophy in Engineering (PhD) Eligibility: All qualified candidates (both UK and International students) Award
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Please quote reference: Quantum Computing at The School of Physical Sciences Duration: 3 years and 6 months. We are currently recruiting for the following full-time, fully funded PhD studentship
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biology, and biochemistry. Plan, conduct, and contribute to experimental work. Identify and develop relevant methods for data collection, analysis, and interpretation. Develop expertise across scientific
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exercise science, human nutrition, human physiology, biochemistry, food science or a related subject. A relevant Master’s degree and/or experience in one or more of the above subjects will be an advantage
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such approaches would be cost effective. To achieve this, you will be supported to undertake analyses using large data registries such as the Clinical Practice Research Datalink. This is an exceptional opportunity
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, including SuperMagdrive, operates using metallic propellant, offering density, integration, and safety advantages compared to conventional launcher propellants such as hydrazine. However, metal propellants
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existing data analytics tools will help deploy these technologies in the industry context without the need for big datasets. Predictive Maintenance (PdM) is one of the maintenance strategies that has
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made. The project will involve using routinely collected healthcare data and/or large healthcare datasets such as the Clinical Practice Research Datalink. This is an excellent opportunity for someone