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experimentation and thermodynamics calculations. Establish a high-throughput bulk materials processing route to enable efficient characterisation and parallel testing of multiple compositions. Develop a high
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. neuroimaging, time-series signals, clinical records) for predictive modelling and decision support. Proficiency in programming languages such as Python (and/or Java, C/C++), with hands-on experience using AI
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in a dynamic and collaborative team. In collaboration with the Edinburgh Parallel Computing Centre (EPCC) and our industry partners, the focus of the role is the development of a new solver for
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solvers, e.g. UVLM, DLM, hybrid 2.5D/VLM coupling, free wake methods and vortex particle solvers; or Experience with high-fidelity solvers, e.g. SU2, OpenFoam, StarCCM+, Fluent; Proficiency in programming
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methane exchange in upland trees drawing on information derived from parallel field studies spanning a rainfall gradient in Ghana (and elsewhere) and modify empirical models of tree methane exchange