37 parallel-computing-numerical-methods-"Prof" PhD positions at Cranfield University in United Kingdom
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We are seeking a highly motivated candidate to undertake a PhD program titled "3D Temperature Field Reconstruction from Local Temperature Monitoring in Directed Energy Deposition." This exciting
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trustworthy operation of navigation systems in complex, GNSS-denied scenarios. The ultimate goal is to provide the navigation research community and industry with tools and methods that ensure continuous, high
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operation costs significantly. Besides, there is an opportunity to explore the commercialisation paths of the developed smart sensor prototype. You will gain from the experience in numerous ways, whether it
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deploy these technologies in the industry context without the need for big datasets. You will gain from the experience in numerous ways, whether it be transferable skills in the technical area of
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combustion environments. Alternative fuels have a different chemical composition from natural gas, which would change depending on the production method used. These unique compositions would translate
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. However, inefficiencies in wind turbine control and maintenance lead to increased operational costs and reduced energy output. Traditional maintenance methods rely on reactive or time-based servicing, which
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algorithms are used that allow a computer to process large data-sets and learn patterns and behaviours, thus allowing them to respond when the same patterns are seen in new data. This include 'supervised
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validated surface functionalisation methods that significantly improve metascintillator performance, accelerating the development of advanced radiation detectors for ToF-PET and enhancing early cancer
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-the-loop testing, and advanced AI methods will further enrich the student’s research experience. The student will have the opportunity to join a vibrant community and team of researchers. This project will
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
. This PhD project will tackle that challenge by developing intelligent methods that combine AI techniques such as language models that interpret technical text and knowledge graphs that map engineering