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Field
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batteries, which differ in state of health, capacity, and interface standards. Furthermore, spatial constraints in dense urban environments, coupled with regulatory uncertainties surrounding battery transport
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involves modelling wind flow across various spatial and temporal scales to improve accuracy. It aims to combine small-scale atmospheric phenomena, such as turbulence, with larger-scale weather patterns and
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will develop novel machine learning and artificial intelligence (ML/AI) methods for genomics data, especially: large-scale single-cell genomics data, high-definition spatial genomics, digital pathology
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Earth system models on different temporal and spatial scales to answer key questions of global change. Doctoral candidates of the IMPRS-ESM contribute to the development and application of Earth system