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Field
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critical to ensuring the longevity and safety of fusion reactors. This PhD project focuses on developing an integrated framework that combines cutting-edge computational models, including Monte Carlo
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compatibility with traditional composite matrices. Explore complementary computational fluid dynamics-discrete element method (CFD-DEM) simulations as a tool to predict fibre-fluid interactions and inform
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. Early diagnosis and an accurate characterization of disease progression are critical for treatment and improving patients' quality of life. However, current methods rely on expensive and time-consuming
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alongside numerical simulations relying on high-performance computing and reduced order modelling. We aim to gain new insights about the physical coherent structures which are most relevant to viscoelastic
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University of Strathclyde will lead the wind energy training and research elements of the programme. Funded by ESB and EPSRC, this 4 year this PhD studentship, at the University of Strathclyde is in the area
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annotations are scarce or unreliable. Recently developed unsupervised learning methods allow to circumvent this limitation by learning patterns in unlabelled medical images and then leveraging them
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with a background in cognitive psychology, data science or computer science and a willingness to develop skills in computational models of cognitive processes, statistical methods, and programming (R
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disturbances. This programme of doctoral work will investigate the prevalence of iron deficiency/ iron deficiency anaemia in high performing athletes and assess the effectiveness of a novel oral iron supplement
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advanced simulation methods, including Reynolds-Averaged Navier-Stokes (RANS), Direct Numerical Simulations (DNS), and/or Large Eddy Simulations (LES), will be employed to accurately model the complex flow
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Primary supervisor - Prof Kate Kemsley Join us to research and develop advanced analytical methods for tackling food fraud head-on! Economically motivated adulteration of foods is a significant