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collaborative IoT scenarios; ii) strategies for efficient and adaptive learning on-device or across a network of heterogeneous nodes while minimizing energy consumption and bandwidth usage; iii) investigating how
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(Conservation Heritage Architecture, buildings and sites by Resilient Methods: hydro-climate factors), financed by European Research Executive Agency under action HORIZON MSCA Doctoral Networks. This project aims
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Agency under action HORIZON MSCA Doctoral Networks. Supervisor: Angelo Giuseppe Landi, Politecnico di Milano - IT (academics) Co-Supervisor: Chiara Bertolin, NTNU (academics) Mentor: Chiara Bondioni, Musei
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precision. By harnessing quantum phenomena such as superposition and entanglement, quantum sensors can detect minute variations in observables such as magnetic fields, electric currents, temperature
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for Enhancing Decision-Making in Networks of Autonomous Agents”, which aims to develop a new methodological framework to improve decision-making in autonomous systems. The project combines high-frequency radio
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Engineering, Communication Engineering, Computer/Data Science, Mathematics or equivalents; – background in artificial intelligence, image/signal processing, remote sensing, passive/active sensors. Where
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to make decisions for localization, navigation, and cooperation. Within the ERC Starting Grant project CUE-GO – Contextual Radio Cues for Enhancing Decision-Making in Networks of Autonomous Agents
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Energy Storage Technologies RESTORATIVE is a pioneering Marie Skłodowska-Curie Actions (MSCA) Doctoral Network dedicated to accelerating the green transition through Thermo-Mechanical Grid-Scale Energy
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within a Research Infrastructure? No Offer Description Neural networks are known to be universal approximants for any function in an arbitrary number of variables. This property has been exploited in
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, including deep learning architectures, self-supervised and unsupervised approaches, physics-informed neural networks, transformer-based models, and/or quantum-inspired learning techniques, capable