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. The student will incorporate the fast-evolving understanding of magma-mush systems into numerical models simulating surface deformation from porous fluid (magma) flow, and test how predicted subsurface stress
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studies of ices or materials. For PhD 3: experience or affinity with numerical modelling, fluid dynamics, or computational physics. Strong analytical skills and the ability to work independently and
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Results: Ability to assess the influence of demise process on the release of emissions into different atmospheric layers. Numerical model to describe the temporal and spatial dispersion behaviour of ablated
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across diverse rock types and integration with predictive models remains lacking. In this PhD study, you will be performing experiments and numerical simulations to understand and predict the clogging
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hard to model with classical computers, it presents a valuable opportunity – to use quantum technologies to efficiently model and simulate other complex systems. Recent focus has been on how we can more
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physical techniques eg laser and optical instrumentation; computational/numerical modelling programming skills eg Python, FORTRAN, C++. Eligibility Open to both UK and International applicants, including EU
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. Project Overview The project focuses on developing and applying advanced CFD models for aeroengine oil systems. There will also be opportunities to integrate machine learning techniques for building lower
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quantitative connections between the continuum parameters and the underlying microscopic mechanics. Numerical study. Implement the models in computational codes to design and optimize morphing strategies. During
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speech at the pinnacle of complexity. Like human babies, songbirds learn their vocalizations early in life from a social tutor. Numerous parallels to human speech learning, including analogous neural
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and night-time low temperatures. There is a need to improve the way the stratified boundary layer is represented (parametrized) in these simulations and also interrogate the models with high-quality