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is promising, but delivers very local measurement only. Therefore, it would be interesting to combine these local measurements with distributed measurements of fluxes that can reveal variations in
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Intelligence (AI) and Machine Learning (ML) capabilities into distributed cloud-edge infrastructures to enable autonomous and efficient network/service management. The PhD candidate will investigate innovative
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department in the ISSA expertise center that develops advanced AI solutions involving AI models, algorithms, implementations, sensors and hardware for small scale edge up to large scale distributed and hybrid
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for next-generation (6G) communication systems. The project focuses on integrating Artificial Intelligence (AI) and Machine Learning (ML) capabilities into distributed cloud-edge infrastructures to enable
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decommissioning schedules, and investment incentives. Analyzing the distributional and societal impacts of the gas phase-out, including inequalities and policy responses (ETS2, Climate Social Fund, etc
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-touch Network and Service Management (ZSM) as a key enabler for autonomous and resilient 6G. The project aims to investigate how network intelligence and automation, distributed core network designs, and
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aims to investigate how network intelligence and automation, distributed core network designs, and AI-driven control loops can improve network robustness, service continuity, and fault tolerance across
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(PacBio HiFi) to build genome assemblies and integrate them into pangenomes. This allowed us to investigate the distribution of structural variants in cattle and related species, construct different
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, distributed systems, or cloud/edge computing. You have at least basic programming skills (e.g., Python, C/C++, or similar). You have good analytical and problem-solving abilities. You have knowledge of 5G
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for the future of mobile and satellite communications. Fields of applications range from 5G/6G telecommunications to satellite-based internet connectivity. For details, you may refer to the following: https