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of information on all the minerals found on the Moon, Mars and in meteorites, and the Machine Learning (ML) software that combines deep learning multi-class and multi-label classification algorithms
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or Associate Professor who is excited to advance the field of Computer Vision and Deep Learning through excellent research, inspiring education, and meaningful collaboration. The Computer Vision Lab conducts
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Hey machine learning enthusiast with a love for physics and
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Hey machine learning enthusiast with a love for physics and complex systems, will you help us develop a new generation of road traffic prediction methods? Job description Road traffic is a highly
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under global change requires accurate and consistent soil information at global scale. Current global soil maps are derived using empirical machine learning that often ignores known soil processes
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A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University , the various disciplines collaborate intensively towards major strategic themes . Our focus is on Dynamics of Youth, Institutions for Open...
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, with a particular focus on the iron and steel sector. By using TROPOMI observations with advanced machine learning techniques, the project will provide independent information on emission patterns and
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, subjective user feedback, and environmental data. The research will involve machine learning, human-centred experimentation, real-time comfort prediction, and the integration of intelligent climate control
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, and environmental data. The research will involve machine learning, human-centred experimentation, real-time comfort prediction, and the integration of intelligent climate control systems into vehicle
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sensing technologies, biomechanical modeling, and machine learning to estimate human joint moments and external disturbances, and to derive robust, activity-agnostic control strategies for stable