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Field
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A PhD studentship is available for commencement October 2026 – January 2027 as part of the first Cohort of a new EPSRC Centre for Doctoral Training in UK Semiconductor Industry Future Skills* led by Swansea University in partnership with the University of Leeds. The PhD studentship will be: 4...
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Application deadline: 30.09.26 Research theme: Applied Mathematics, Thermal-Fluid-Dynamics, Multi-Physics How to apply: https://uom.link/pgr-apply-2425 UK only This 4 year PhD project is fully
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; • mathematical modelling, development of FEM models (preferably using Ansys), and simulations, particularly in the areas of electromagnetics, power losses, etc.; evaluation, verification, and optimization
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might conceptualise and mathematically structure marine socio-ecosystem models if the structure of the system itself can change through time and space. Rather than treating climate change simply as a
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wave equations. In the project, we will develop a new mathematical and computational framework that combines PDE-based modelling with ideas from data-driven reduced-order modelling. The aim is to obtain
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embedded decision-makers who interpret health risks through multiple, often competing, social identities. Traditional epidemic models offer mathematical precision but fail when confronted with this reality
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position: Experience of modelling energy systems, particularly at the national level. Experience of optimisation modelling and/or other mathematical models. Experience in scenario analysis, related
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field closely related to computational modeling in science and engineering. You have a strong background in the theoretical foundations of engineering, science and applied mathematics. It is an advantage
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new approach has emerged that integrates data and mathematical models through neural networks. This has led to the development of a method for solving partial differential equations (PDEs) known as
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evaluate statistical and machine learning models - Publish results in peer-reviewed journals Desired Qualifications - Master’s degree in statistics, mathematics, data science, bioinformatics, physics