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, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and working with large ensembles of climate/weather model output are advantages
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well as experience in atmospheric dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and
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a broad activity within physics with activities in solid state physics/material physics, soft/complex and biopolymer physics, medical physics, statistical physics, optics, atmospheric physics
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legal issues such as the rights to AI-assisted and AI-generated works and compensation for use of existing works in AI model training. In light of this ongoing transformation, it is imperative