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Field
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. Experience in, or willingness to learn data-driven approaches, including artificial intelligence (AI) and machine learning (ML) models, to solve problems. The Successful Candidate Will A curious scholar with a
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on the development of machine learning algorithms, particularly transfer and adaptive learning, for multimodal wearable biosensing and its translation to rehabilitation and digital health applications. It is co
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projects, as well as in multiagent systems, including computational game theory, security games, machine learning in multiagent settings, automated planning under uncertainty, social networks and others
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scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities
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on developing robotics and cyber physical systems solutions using machine learning and artificial intelligence to support different aspects of marine science, with opportunities to expand to other areas
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of statistics and machine learning. Modern vessels produce vast amounts of multivariate data streams. The project addresses the development of trustworthy statistical and machine learning methods for anomaly
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qualification; (ii) demonstrate research skills in imaging science and machine learning, particularly on image reverse engineering, fake image and video detection, statistical detection models and mathematical
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community. Fellows teach one small seminar during their fellowship year appropriate for graduate students and advanced undergraduates. Though courses are designed to fit the focal theme, there are no
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of Oslo’s Department of Informatics (IFI) and is hosted by the Network and Distributed Systems Research Group (ND) with co-supervision from IFI’s Machine Learning section and the University of Inland
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to demonstrate skills on Data Analytics and Machine Learning, in particular on distributed ML. Must have very good programming competence in Python, Java, C/C++ or equivalent Fluent oral and written communication