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disconnectivity in brain networks relates to symptom networks and recovery trajectories in psychiatric patients. Apply and further develop methods from network science, machine learning, and computational
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on Graphs: Symmetry Meets Structure (LOGSMS). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing
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patient-centred organizations across Europe. Through this collaborative, interdisciplinary network, our researchers will work at the frontier of personalized neuroscience. Where to apply Website https
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several critical requirements: first, the geometry and size of the vascular network should be representative of real (tumor) microvasculature, i.e. consisting of 3-dimensional networks of perfusable lumens
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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communication. Join us and apply for one of the two available PhD positions below! Quantum Network Systems The goal of this position is to optimize the design of our quantum network operating system
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the goal of building a multiscale foundation of knowledge that is directly relevant for understanding complex human diseases. This project is part of the TRANSCEND Doctoral Network (https://biomed.au.dk
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Network Up on selection, the PhD Candidates will be part of a prestigious Marie Skłodowska-Curie Doctoral Network “MITIME: Migration and Time in Post-industrial Urban Europe” (see details here MITIME
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translational relevance. This PhD position is part of a Marie Skłodowska-Curie Doctoral Network (Horizon Europe). As a MSCA Doctoral Candidate, you will join a cohort of early-stage researchers across several
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social science / (social) network science to support the growing activities of the newly established Urban Impact Lab and of PLANET-NL, a collaborative inter-university research group. The positions