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Field
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You will receive project-specific training in numerical modelling tools and techniques and in machine learning. Eligibility requirements If you have received a First-class Honours degree, or a 2:1
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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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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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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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. 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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developing a digital twin, employing machine learning and numerical computations of atomistic processes. At IKZ, a kinetic Monte Carlo tool has been developed in the programming language julia. This allows a
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-driven modelling and numerical mathematics leading to computationally fast methods State-of-X (where X is charge, health and/or function) estimation at the pack level. This requires developing
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atmospheres, their origin and how they are expected to evolve in a changing climate. Spectral 2D and 3D numerical solvers based on spherical harmonics will be used for the project to perform simulations aimed
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benchmarking of clay mineral surface finite models for DFT simulations Speciation simulations of the radionuclides in various environments Your profile Completed university studies (Master/Diploma) in the field
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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