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Description Ageing infrastructures, urbanization, and climate change are intensifying the vulnerability of critical infrastructures (CI), high-tech industries (HTI), and communities to cascading hazards
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communities to cascading hazards, particularly NaTech (Natural Hazard Trig-gering Technological) events. REUNATECH is a Horizon Europe Marie Skłodowska-Curie Doctoral Network that aims to educate and train the
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Communication models within timing constraints in quantum applications Algorithms and protocols for joint transfer of digital data and entanglement Networked quantum sensing supported by distributed classical
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, the project implements an approach combining social, institutional, and digital history across three work packages: (i) Communities, (ii) Hierarchies, and (iii) Infrastructures. To operationalize its approach
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-tasks and language models. This position is part of SDU’s initiative to develop energy-efficient AI accelerators based on alternative model architectures that cannot be leveraged as efficiently
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between substance-use and (digital) culture, focusing on the interconnections between legal and illegal transactions and trajectories related to prescription tranquilizers. The project contains three parts
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University of Munich (TUM) , focusing on cutting-edge research in digital health, wearable sensing, and embedded artificial intelligence. The Project title is ‘IoT-based Assisted Living’ and the main purpose
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applications Co-integration of SSM-SNN cores with RISC-V processors in CMOS Hybrid analog/digital interfaces for spike generation and propagation Event-based communication protocols for ultra-low-power operation
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, you will join the Power-to-X and Storage (PtX) section within the Power and Energy Systems (PES) division. The PtX section combines multidisciplinary research in energy storage and flexibility, digital
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Digital Twins for Wind-Offshore and GREAT: GRid Enhancement for Ancillaries in Tomorrow’s power systems, where you will interact with researchers and experts from TotalEnergies and many other research