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noradrenergic signaling. In close collaboration with the University of Oxford, we combine cutting-edge computational modeling of human behavior with pupillometry and functional magnetic resonance imaging (fMRI
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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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Your position The candidate will have the opportunity to exploit some of the cutting-edge experimental and computational methods, comprising constraint-based and kinetic modeling, statistical
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qualitative and quantitative analytical methods to model clinician attention, verbal reasoning, and documentation behaviour Develop and evaluate machine learning models, including unimodal, fusion, and
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Your position The candidate will have the opportunity to exploit some of the cutting-edge experimental and computational methods, comprising constraint-based and kinetic modeling, statistical
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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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phenotyping research focuses on the development of methods and models to determine traits of relevance for crop breeding and variety testing. The Agroscope research group Extension Arable Crops (Competence
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of soil erosion and land management in phosphorus transport and eutrophication, using monitoring data from the EU Water Framework Directive to calibrate and validate advanced sediment routing and modelling
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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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of your master's thesis), and (iv) transcripts and diplomas of your bachelor's and master's degrees (if available) via our online recruiting platform. If you use large language models or other artificial