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an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the following computing skills will be considered an advantage: Natural
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an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the following computing skills will be considered an advantage: Natural
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important for renewable energy production and production variability will be an advantage. Knowledge of machine learning or optimization will be an advantage. Applicants must be able to work independently and
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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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PhD Research Fellowships: Artificial Intelligence Adoption, Sustainable Finance, and Twin Transition
knowledge of artificial intelligence and knowledge of natural language processing. Proficiency in statistical analysis, such as econometrics and machine learning for survey data analysis. Experience with data
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or equivalent in cognitive science, computational science or machine learning with a STEM focus. Foreign completed degrees (M.Sc.-level) must correspond to a minimum of four years in the Norwegian educational
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-scale assessment data, meta-analyses of meta-analyses) Methods and approaches to cumulative, living, and community-augmented meta-analyses Methods and approaches to include machine learning and artificial
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, with interests spanning a broad range of areas - including statistical machine learning, high-dimensional data and big data, computationally intensive inference for complex models, causal inference and
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engineering, engineering computing, sensor networks and measurement technologies, grid computing and physics data analysis, machine learning, and interactive and collaborative systems. The prospective PhD