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Field
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framework exploiting the use of physical and geometrical conservation laws in a variety of spatial discretisation schemes (i.e. Finite Element, Finite Volume, Meshless). The resulting conservation-type
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have an excellent PhD in biomechanics (or a related discipline), possess a solid knowledge of non-linear finite element modelling, have a strong experience in developing and validating patient-specific
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and accelerated brain aging by coupling mechanics and neurobiology to create multiphysics-informed predictive models of brain health. Specifically, our approach combines finite element modelling and
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Using finite element modelling (FEM) to simulate different hole configurations and validating these models with cadaveric femur specimens, this study will provide crucial insights to optimise
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Digital Image Correlation and stress wave analysis, and the development of custom material subroutines within finite element software to accurately reflect experimental observations. This is a hands-on
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publication Strong programming skills and familiarity with machine learning or finite element modelling Not currently receiving another scholarship of equal or higher value Application process Future student
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fields, and risk damaging the part during fabrication. Finite element analysis (FEA) models, while capable of delivering detailed spatiotemporal distributions of thermal variables, suffer from limited
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This PhD project will focus on developing AI-based methods to accelerate the Swansea University in-house discontinuous Galerkin (DG) finite element solver for the Boltzmann-BGK (BBGK) equation
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demonstrate these in their application materials Familiarity with numerical methods for PDEs (e.g., finite difference or finite element methods) Experience with tissue simulations and/or HPC is a plus Interest
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biology, or applied mathematics Documented experience in C++ programming and solid software engineering fundamentals Familiarity with numerical methods for solving PDEs (e.g., finite difference, finite