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to coordinate and conduct asset management and maintenance activities across infrastructure networks in the Netherlands. Together with our research partners from Next Generation Infrastructure network, the PhD
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collaboration with the Interfaces and Correlated Electronics (ICE) group at the University of Twente and the Infomatter group at AMOLF. The SMIP project aims at revolutionising computing by developing adaptive
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PhD position on Closed-loop testing for faster and better EM evaluation of complex high-tech systems
-Curie Project NEPIT - Network for Evaluation of Propagation and Interference Training. To expose objects to electromagnetic fields we step to a new position, increase power level until a defined value is
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AI models for network operations. This project is a joint effort between the University of Twente and TU Delft. You will be co-supervised by Associate Prof. Pedro P. Vergara from TU Delft and
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operations research, algorithmic discrete mathematics, complex networks, statistics, systems theory, computational science, and artificial intelligence with applications in health care, energy systems, traffic
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benefit from a strong cultural awareness and the ability to engage with broad networks of governmental and community actors in the planning of future urban spaces. Specific case studies will be shaped with
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of Applied Science, supervisors from the Construction Management Engineering cluster at the University of Twente, and a strong network of industry partners in the Dutch construction sector. Information and application
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Universities of Applied Science, supervisors from the Construction Management and Engineering cluster at the University of Twente, and a strong network of industry partners in the Dutch construction sector
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Engineering cluster at the University of Twente, and a strong network of industry partners in the Dutch construction sector. The expected starting date for this position is January 2026. Information and
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medicine. As a PhD student, you will: Build computational models that integrate molecular and genetic data to study possible OA treatments. Develop bioinformatics pipelines, network-based approaches