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develop (physics-informed) hierarchical graph neural network architectures that can capture the complexity of multi-scale urban energy infrastructures. The PhD will explore how these models can represent
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, reliability, and availability of complex industrial systems while making maintenance strategies more cost-efficient. Together, UESL and IMOS are seeking a motivated and qualified PhD candidate to advance
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