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for a researcher as of the Feb. 1st, 2026 (PhD position) as part of the reserach project BANNER. Your tasks: Develop AI algorithms for real-time fault detection, fault classification, and failure-mode
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(CAITE) whose aim is twofold. First, it aims to bring AI at the edge, by providing scalability and resource efficiency through the development of cooperative, distributed AI algorithms, optimising data
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refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . Your role The successful candidate will join the SIGCOM Research Group, led by Prof. Symeon Chatzinotas. This PhD project aims to develop
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the 01.02.2026 at the following conditions (PhD position): 50% = 19,92 hours Pay grade 13 TV-L limited 30.11.2028 Your tasks: Develop AI algorithms for real-time fault detection, fault classification
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Description Challenge: Uncovering the interdependency between telecommunications networks and urban infrastructures Change: Developing data analysis and modelling methods to understand the interdependency
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. Your duties and responsibilities include: Development of a flood classification framework for flood type prediction Comparison of different ML algorithms in a sensitivity study Communication with
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, privacy, and resilience. Today’s Transformers models scale poorly and assume abundant cloud resources. The research program FIND aims to deliver architectural and algorithmic breakthroughs that enable
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functions). Explore model-based RL approaches that integrate learned models with planning and adaptation mechanisms. Hybrid Evolutionary-RL Framework Develop novel frameworks with evolutionary algorithms
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transformations. The project investigates a hybrid approach that combines deep learning with grammatical inference to develop models that are interpretable, efficient, and mathematically verifiable while leveraging
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) and the University of California Irvine (UCI). The Research School "Foundations of AI" focuses on advancing AI methods, including energy-efficient and privacy-aware algorithms, fair and explainable