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- Delft University of Technology (TU Delft); today published
- Delft University of Technology (TU Delft); yesterday published
- Eindhoven University of Technology (TU/e); today published
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on the topic of understanding and predicting the dynamics of complex engineering systems in order to develop advanced control, estimation, planning, learning and diagnostics strategies which are at the core
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collaboration and easy access to key application domains, unique infrastructure, and other computer science researchers. On the VU campus, we have organized multidisciplinary collaborations like the Network
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Radboud University Medical Center (Radboudumc); yesterday published | Netherlands | about 18 hours ago
interaction between fundamental research and the treatment of (complex) patients so clearly present, and the potential for impact on both patients and healthy people so great. AI, e-health and medical
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. The mission of the Dynamics and Control Section is to perform research and train next-generation students on the topic of understanding and predicting the dynamics of complex engineering systems in
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economics/social sciences, network flows, agent-based approaches, integrated systems, holistic design. Application of advanced mathematics such as complexity theory, mean field game theory, or statistical
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such as: managing and maintaining: complex network infrastructure (e.g., configuring firewalls, VLANs, LACP, etc.) advanced compute infrastructure (e.g., supercomputers, GPU machines, Slurm) Linux systems
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tasks such as: managing and maintaining: complex network infrastructure (e.g., configuring firewalls, VLANs, LACP, etc.) advanced compute infrastructure (e.g., supercomputers, GPU machines, Slurm) Linux
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loads, inclusive markets and technology, complex ownership, and power assets connected via power electronics. New and unsolved phenomena such as swarm behaviour of smart power prosumers (consumers and
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communication networks is an essential requirement for all modern security applications. State-of-the-art methods for secret key generation and storage have been developed which are based on fuzzy sources, e.g
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developed into strong and long-term relationships. This network is continuously engaged to find potential matches between internal research interests and external research needs as well as matches