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while maintaining energy production efficiency. The integration of machine learning (ML) in predictive maintenance has transformed hydroelectric operations by enabling data-driven decision-making and real
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to develop highly automated tools to aid decision-makers facing the future challenges of the NBM. Meanwhile, AI and Machine learning techniques offer new opportunities to revolutionize the design and operation
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Position as PhD Research Fellow in machine learning available at Department for Informatics with the research group Digital Signal Processing and Image Analysis (https://www.mn.uio.no/ifi/english/research
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Postdoctoral position in Natural Language Processing (NLP) is available at MediaFutures in the Language Technology Group (LTG) within the Section for Machine Learning at the Department of Informatics, University
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Research Fellow in machine learning available at the Department for Informatics with the research group Digital Signal Processing and Image Analysis (https://www.mn.uio.no/ifi/english/research/groups/dsb
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biostatistics groups with currently ca 75 researchers. OCBE is internationally recognized, with interests spanning a broad range of areas - including statistical machine learning, high-dimensional data and big
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be employed by any other institution for the time of the fellowship. Experience with AI-related research and/or innovation is an advantage. Experience in machine learning is a requirement. Experience
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. Experience with AI-related research and/or innovation is an advantage. Experience in machine learning is a requirement. Experience with programming and app development will be emphasized The LEAD AI mobility
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the field of geoscience? Improve deep learning methods for multi-modal image data applied to industrial challenges in the energy sector? Contribute to a deeper understanding of the composition of the crust
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programming (e.g. Python) is a requirement. Experience with machine learning is an advantage. Experience from free energy calculations is an advantage. Applicants must be able to work independently and in a