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description The functioning of cities depends more than ever on urban infrastructures like transportation networks, power grids, water networks, Internet of Things sensors, and analytics platforms that gather
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hidden patterns from them? Do you enjoy exploring mathematical models and working with network data? Join our team! Job description Complex systems are often modeled with networks, structures where
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of the Marie Curie Doctoral Networks "FINALITY", will be hosted at TU Delft, Department of Computer Science, and will be co-supervised by Prof. George Iosifidis (TU Delft) and Prof. Constantine Dovrolis
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and spatially complex nature of MRI signals. Each MRI examination involves multiple pulse sequences, with signal acquisition being sensitive to coil placement, sensor geometry, B0/B1 inhomogeneities
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networks, Internet of Things sensors, and analytics platforms that gather data from those infrastructures, as well as telecommunications networks. To fully support the operation of cities, telecommunications
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future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which
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lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future
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-efficient digital AI/ML accelerator for real-time transmitter error correction in high-speed RF systems. Co-design and validate on real silicon. Job description Wireless networks are becoming increasingly
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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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simulation methods, which generate photorealistic sensor feedback after each action. Achieving this requires novel view synthesis techniques that enable realistic simulation from previously unseen viewpoints