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57,000/year Collaboration with an internationally recognized research team with leading experts in remote sensing, atmospheric modelling, emission quantification, and machine-learning. Integration
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recognized research team with leading experts in remote sensing, atmospheric modelling, emission quantification, and machine-learning. Integration into Empa's Atmospheric Modelling / Remote Sensing group with
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real