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to work with modern massively-parallel simulation codes. Candidates must have (or be close to completion of) a PhD in astrophysics or a related subject, and a BSc/MPhys (or equivalent) degree in physics
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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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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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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