53 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "University of St" "St" "St" Postdoctoral positions in Luxembourg
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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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complete application in English via https://jobs.liser.lu/jobs by including the following documents before April 15th, 2026 : Curriculum vitae ; Motivation letter ; Recent piece of research ; Copy of your
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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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solutions that address real-world challenges and create positive impact. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? As part of a major European
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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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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
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curiosity, innovation and entrepreneurship in all areas · Personalized learning programme to foster our staff’s soft and technical skills · Multicultural and international work environment with
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-performance computing resources suitable for large-scale machine-learning and foundation-model experiments. Your role We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025
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our website: https://www.list.lu/ How will you contribute? LIST is seeking to recruit a two-year postdoctoral position to work on fabrication of the piezoelectric energy harvester based on ceramics
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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