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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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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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neuronal network function and how recovery can be enhanced, with the eventual goal to translate findings to the clinic. We are currently developing a stable, long-term, high-throughput experimental system
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occurs; and validating these approaches against community and industry benchmarks. The work combines network measurements, data science, and systems security, with an emphasis on reproducibility and real
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. Engin Topan. In high-mix, low-volume manufacturing, traditional planning often fails to capture workload variability, uncertainty, and the complex interaction between product features, labor availability
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performances the in-capsule organoids formation. Moreover, you will pioneer the annealing of the organoid-forming microgels into large microporous living materials that contain perfusable capillary-like networks
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the worlds of people and technology to address today’s complex societal challenges. We are passionate about understanding human behaviour, fostering responsible innovation, and designing solutions that create
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problematic social and political dynamics that discourage national support and spark local opposition to the renewable energy projects energy communities are involved in. The resulting complex social dynamics
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PhD candidate to (1) explore to what extent such high fidelity supports or hinders (groups of) people in grasping cause–effect relationships of world adaptations and system complexity; and (2) design
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novel system that integrates smart carriers into complex rubber matrices. Your main research activities will revolve around: 1. System Formulation and Design: Developing novel protective systems using