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students as well as 300 professors, the University distinguishes itself with its international and multilingual character, an interdisciplinary approach, and a personalised learning environment. The
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The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg is a leading international research and innovation centre...
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The successful candidate is expected to assume a leading role in defining, acquiring, managing, and scientifically contributing to projects in Reinforcement Learning on Space Robotics. The candidate
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machine learning technologies to provide evidence-based decision support tools in near real time across a variety of thematic domains: disaster risk reduction, sustainable agri-food systems, terrestrial
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biotic and abiotic resources. We integrate remotely sensed information with in-situ data, process-based models and leverage satellite communication, IoT and machine learning technologies to provide
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communication, IoT and machine learning technologies to provide evidence-based decision support tools in near real time across a variety of thematic domains: disaster risk reduction, precision agriculture
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communication, IoT and machine learning technologies to provide evidence-based decision support tools in near real time across a variety of thematic domains: disaster risk reduction, precision agriculture
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) from ETHZ led by Prof. Marco Hutter to carry out research to pursue a PhD on the following topic: Machine Learning for anomalies/failures detection, identification and prediction on mobile and legged
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Applications should include: Curriculum Vitae Cover letter Research statement on planned future research topics and strategy Early application is highly encouraged, as the applications will be processed upon reception. To ensure full consideration, candidates should apply by 15th March 2025...
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) position in Computational Fluid Dynamics. Advances in computational sciences, machine learning, and artificial intelligence are transforming the study of complex flows. Such systems are prevalent in both