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energy system models that incorporate a stronger Social Sciences and Humanities (SSH) perspective. By embedding societal dynamics, such models aim to capture a wider range of future uncertainties and
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the complexity of multi-scale urban energy infrastructures. The PhD will explore how these models can represent spatial and temporal dependencies in systems, such as building energy demand, district
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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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plumes from point sources using the MicroHH atmospheric model. Analysis of plume dynamics and NOx chemistry in the high-resolution simulations. Develop and refine data-driven methods for emission
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activation and micromechanical modeling Progressive damage modeling of reinforced FRPs Mechanical characterization and fracture experiments Complete a PhD thesis at ETHZ Your profile Highly motivated and
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the MicroHH atmospheric model. Analysis of plume dynamics and NOx chemistry in the high-resolution simulations. Develop and refine data-driven methods for emission quantification. Apply your methods to real
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, technologies and systems. The ERAM group within TSL have great experience in SSbD, especially in combining different methods such as modeling mass flows analysis (MFA), Life cycle analysis (LCA) and semi
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and flow field interactions Tuning of the CFD models with experimental results Artificial Neural Network training and development Scientific publications in journals and at conferences Supervision
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different methods such as modeling mass flows analysis (MFA), Life cycle analysis (LCA) and semi-quantitative methods for decision support for sustainable innovation. PhD Student in Safe and Sustainable Green
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field interactions Tuning of the CFD models with experimental results Artificial Neural Network training and development Scientific publications in journals and at conferences Supervision of students Your