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system models to analyse whether spatially coherent urban and energy configurations can be operated efficiently under realistic physical, spatial, and infrastructural constraints. The work aims to identify
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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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14 Feb 2026 Job Information Organisation/Company Empa Research Field Computer science » Other Engineering » Other Mathematics » Applied mathematics Technology » Energy technology Technology
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