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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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frameworks (e.g. PyTorch, TensorFlow) and relevant libraries. Practical experience in scalable data processing, including the use of parallel computing, cloud platforms, and distributed systems for efficient
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Bayesian approach (Lages, 2024). Techniques used: Computational modelling, Bayesian inference, sampling and simulation techniques, prior distributions and posterior predictive checks, model comparison
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team. Work towards achieving the Objectives will run in parallel through the project, broadly along the following timeline: Year 1: literature review, desk-based mapping, initial fieldwork mapping and
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well as community function, to be investigated in parallel. Standard geochemical analyses will be simultaneously performed to investigate interactions between the major nutrient cycles, and their impact on