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physics, the development of innovative analytical and numerical methods, strong research outputs, and active contribution to the Centre's collaborative research environment. Qualifications Required PhD in
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practice (e.g., Python/MATLAB/C++ and/or established modelling platforms). Familiarity with asymptotic and multiscale mathematical analysis methods to ground proof numerical simulations Strong communication
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. Relevant tasks include mathematical modelling and development and implementation of numerical methods for reactive thermal multiphase flow, and investigation of cases relevant for understanding processes in
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Bring your expertise in analytical and numerical spray modelling to the University of Brighton’s Advanced Engineering Centre, where you’ll play a key role in advancing cutting-edge two‑phase flow
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%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model
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of the entire reprogramming process, from the sourcing of somatic cells to the final characterization and banking of high-quality, pluripotent lines. This expertise involves mastering numerous
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the group can test and validate models of sodium-ion battery behaviour. As such, proficiency in computer programming (particularly python) is required as well as knowledge of numerical methods
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Experimental structural testing and instrumentation Numerical modelling and simulation AI/data-driven methods for engineering applications Familiarity with engineering software such as ABAQUS, ETABS, MATLAB
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an opportunity to contribute to a collaborative international research environment. GIANTS is a five-year theoretical and numerical modelling project focused on the late stage of terrestrial planet formation
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at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model reduction, with