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modelling, data assimilation, and multi-scale neural network architectures applied to spatio-temporal data. The development of these methods is motivated by a concrete and important application: inferring gas
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enablers for predicting and reasoning about dynamics and transport patterns, in turn being of key importance for a broad range of human activities. The research in the PhD project will focus on core spatio
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