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dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and working with large ensembles
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modelling, data-driven climate modelling, and working with large ensembles of climate/weather model output are advantages. The LEAD AI mobility rules must be followed. Outgoing fellowships require
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work upon. Suggested reading to explore this line of research further: Kitto, K., Hicks, B., & Buckingham Shum, S. (2023). Using causal models to bridge the divide between big data and educational theory
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., Hicks, B., & Buckingham Shum, S. (2023). Using causal models to bridge the divide between big data and educational theory. British Journal of Educational Technology, 54(5), 1095-1124. Swist, T., Gulson, K
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climate change are far-reaching, particularly when it comes to identifying and interpreting trends in regional-to-local scale signals and extreme events. Large ensembles of climate simulations are a key