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with strong expertise in machine learning for cyber-physical systems and a solid understanding of electric power distribution systems, and microgrid operations. The selected candidate will develop and
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Woods Hole Oceanographic Institution | Woods Hole, Massachusetts | United States | about 1 month ago
outputs, developing and evaluating machine learning methods for sound processing (including deep learning approaches such as convolutional neural networks and transformers), and testing detector performance
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(graduated or close to graduation) in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, Applied Mathematics, or related fields. Scientific curiosity and creative thinking
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aspects of machine learning focusing on efficiency, generalization, and sparse neural networks. Currently we are expanding our expertise by applying our theoretical findings also to robotics. Hybrid is our
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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 innovationcentrein...
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We are looking for a highly motivated PhD candidate interested in AI-based methods, including machine learning and language technologies, for the integration and analysis of clinical, advanced data
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UiO/Anders Lien 24th April 2026 Languages English English English Postdoctoral position in Machine Learning and Computational Biology Apply for this job See advertisement About the position
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/Anders Lien 24th April 2026 Languages English English English Postdoctoral position in Machine Learning and Computational Biology Apply for this job See advertisement About the position Applications
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, in Statistics, Computer Science, Applied Mathematics, or a related field. Some research background in Statistics or Machine Learning. Entry level candidates are welcome to apply Technical Competencies
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image processing, disease detection, diagnosis, and therapeutic monitoring. The program addresses critical regulatory challenges posed by AI devices that can continuously learn and adapt, including