131 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions in Luxembourg
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, machine learning, robotics, aerospace engineering, and/or image/signal processing Experience with European, national, and/or industrial projects A solid mathematical background Proficiency in Python, Matlab
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on neurodegenerative processes and are especially interested in Alzheimer’s and Parkinson’s disease and their contributing factors. The LCSB recruits talented scientists from various disciplines: computer scientists
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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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The ideal candidate applies machine learning and big data techniques to important questions in economics, combining advanced computational methods with sound economic theory to uncover insights
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, Reasoning and Validation (Serval) research group and work on a research project related to the application of machine learning for official statistics. The subject of the thesis will be “Exploring Large
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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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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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car simulator facilities. Work in the project comprises human-factors research, artificial intelligence and data analytics. Do you want to know more about LIST? Check our website: https://www.list.lu
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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