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Fully-funded PhD Studentship: Adaptive Mesh Refinement for More Efficient Predictions of Wall Boiling Bubble Dynamics This exciting opportunity is based within the Fluids and Thermal Engineering
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading academics from 5 universities, and 11
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will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading academics from 5 universities, and 11 industry leaders in pharmaceutical
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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Institutes (Research Institutes of Sweden) to large industrial manufacturers (UPM-KYMMENE ). The student will also work alongside a Postdoctoral researcher at Nottingham to design and create small scale
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to another that can be viewed as heteroclinic connections between phase-locked states. The PhD project will consider the role that communication delays between nodes can have in shaping patterns of dynamic
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, usability, and insight into leakage dynamics across diverse constructions. Research Objectives The project is structured around three synergistic work packages: Descriptive Analytics: You will conduct a