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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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learning methods to study structural transformations taking place at the atomic scale via accelerated simulation. The new methods will be used to study pyrolysis and relaxation processes in glasses. Your
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2019 https://doi.org/10.1038/s41596-018-0110-x and Lara et al ., arXiv:2503.21396 https://doi.org/10.48550/arXiv.2503.21396 )). In parallel with your experimental work, you would develop theoretical
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shrimps. In parallel with your experimental work, you would develop theoretical models in collaboration with our international collaborators. You would also develop advanced image analysis schemes
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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