131 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions in Luxembourg
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/performance trade-offs and typical RAN levers; experience with energy metering data is a plus. • Strong background in AI / Machine Learning for decision-making (e.g., forecasting, optimization with learning
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Are you passionate about cutting-edge research in Computer Vision and Artificial Intelligence? Our research group CVI2 - Computer Vision, Imaging and Machine Intelligence, headed by Prof. Djamila
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, modelling and implementation of security protocols with classical, post-quantum, and quantum cryptography. For further information, you may refer to https://www.uni.lu/snt-en/research-groups/apsia
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and textual conditions Primary experiments will be conducted in CARLA (https://carla.org), enabling controlled and repeatable evaluation of hallucinations under diverse driving conditions. The PhD
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https://www.uni.lu/snt-en/research-groups/trux/ . The successful candidate will: Conduct cutting-edge research in multimodal and multilingual natural language processing Develop and curate multimodal
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satellite communications. Fields of applications range from 5G/6G telecommunications to satellite-based internet connectivity. For details, you may refer to the following: https://wwwen.uni.lu/snt/research
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entertainment systems, cybersecurity, and more. For more information, you may refer to https://www.uni.lu/snt-en/research-groups/trux/ . The person will: Conduct cutting-edge research across software engineering
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Specialist will be a member of the Department of Geography and Spatial Planning (https://dgeo.uni.lu ), joining the Economic Geography team of Prof. Christian Schulz. The position contributes to the INTERREG
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3GPP compliant 5G/6G NR NTN OFDM waveforms Develop and analyse signal processing and/or machine learning algorithms for joint channel, delay, Doppler and carrier phase estimation, remote object ranging
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if they demonstrate strong relevant skills. Coursework or strong background in computational mechanics / FEM, numerical methods, and scientific programming. Exposure to machine learning / data-driven modelling and/or