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research network called NiteLiDAR. We want to use the results of this research, together with our partners, to create innovative demonstrators for the next generation of LiDARs. In the second step you will
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an emphasis on software systems. Prior expertise in operating systems is desirable. Prior knowledge in quantum technologies is a plus, but not required. Quantum Network Applications The goal of this PhD
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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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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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Vacancies 2x PhD positions in the Mathematical Foundations of Machine Learning on Graphs and Networks Key takeaways The Discrete Mathematics and Mathematical Programming (DMMP) group
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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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Optimization group within the Delft Institute of Applied Mathematics at TU Delft is offering a full-time PhD position in the area of mathematical phylogenetics. Phylogenetic networks are directed acyclic graphs
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member of the MOMENTUM NextGen Early Career Research Network, which facilitates the integration, training and collaboration of PhDs and postdocs in the Netherlands as part of their career development as
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of PRIDE observables with conventional radiometric tracking data. Your work will bridge radio data analysis, planetary science, and software development, and will directly contribute to improving
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PhD candidates, postdocs, and societal partners across the consortium, including participation in the Professional Learning Community. Participate in DECIDE training programs, workshops, and summer