129 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" positions in Luxembourg
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The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. To be at the forefront of innovation in teaching and learning
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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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The successful candidates will join the Computer Vision, Machine Intelligence and Imaging (CVI2) research group, led by Prof. Djamila Aouada, to conduct research in Artificial Intelligence with a
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generation, media forensics, anomaly detection, multimodal learning with an emphasis on vision-language models, computer vision applications for space. Key responsabilities: Shape research directions and
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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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, management, economics, and other fields, united by a shared commitment to advancing sustainable technologies that benefit society. For more information, please visit our website: https://www.uni.lu/snt-en
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Swarm Intelligence, Reinforcement Learning and Optimization Techniques. As a Postdoctoral researcher, you will: Lead cutting edge research in Swarm Intelligence and Machine Learning, addressing challenges
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of the PhD will be the derivation of multilayered approaches for motion planning and control based on the XS-Graphs, where both model-based and learning-based solutions are foreseen. This includes
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Machine Learning, addressing challenges in counter drone swarm formation and defense Design, develop and conduct experiments of drone swarms using both simulation environments and real-world deployments
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and