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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
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integrated in a removable smart denture. The project targets the integration an advanced micro-system comprising sensors, micro-fluidics, and a sophisticated drug delivery system. The complex 3D printed
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probe microscopy. Our research focuses on using single electron spins in diamond as sensors to explore magnetic phenomena at the nanoscale. This doctoral project will center around the development and
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, based on measured air temperature and humidity data in cold chains by commercial sensors, and deploy them in end-to-end virtual supply chains. This project also aims to optimize other thermal processes
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some products decay faster. For that purpose, we develop digital twins of the cargo, based on measured air temperature and humidity data in cold chains by commercial sensors, and deploy them in end
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single electron spins in diamond as sensors to explore magnetic phenomena at the nanoscale. This doctoral project will center around the development and application of scanning magnetometry at ultra-low
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-Curie (MSCA) doctoral network led by Prof. Persson, Uppsala University. This network has 8 doctoral candidate host institutions: Uppsala University, Universitat Politecnica de Catalunya, Dublin City
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Description As part of a new EU MSCA Doctoral Network ELEVATE (101227453), we are offering a PhD Position on “Modulating bursting activity in silicon neurons to control plasticity and attention”. Location
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Group in the Social Networks Lab at ETH Zürich is developing network data science methods and applying them in a variety of domains. Our current research focus is on sports analytics and we seek to expand