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programme that will train the next-generation of doctoral carbon champions who are renowned for research excellence and interdisciplinary systemic thinking for Net Zero. The ReNU+ vision is that they will
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the group of computational aerodynamics and aeroacoustics (CA^2) led by Dr Zhong-Nan Wang at the University of Birmingham. The CA^2 research group focuses on developing high-fidelity Computational Fluid
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conventional analysis methods struggle. The work is inherently interdisciplinary, combining elements of experimental NMR, chemical kinetics, mathematical modelling, and computational data analysis, and the
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mechanics, and analytical and numerical methods to solve partial differential equations. Excellent oral and written communication skills. Prior experience in computational fluid dynamics or active matter will
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necessarily require formal education in geotechnics. Applicants with a background in mechanical/materials engineering or alternatively mathematics/computer science with an interest in numerical modelling
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will be imaged across different field and thermal histories using MFM, magneto-optical Kerr effect (MOKE) imaging, and synchrotron-based X-ray magnetic circular dichroism (XMCD). In parallel, electrical
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sensing (e.g., PlanetScope, Sentinel-1), advanced numerical modelling (HEC-RAS, Delft-FM), and targeted field surveys to map mining intensity, simulate channel adjustment, and assess changing flood hazards
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profound interest in inorganic chemistry, both in experimental and modelling applications. We are looking for candidates who are also interested in the analytical and numerical aspects of the work
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on understanding what is essential for multimodal learning when computation, memory, or energy are limited. Rather than scaling up models, the research aims to identify principled, lightweight methods
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overall, 6 in each category). Acceptable first degree: Computer Science/Physics/Maths or other numerate discipline. Mode of Study Full-time Start Date 1 October 2026 Funding Information ARIES studentships