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Field
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, brain science, and neuroscience); data science and machine learning; modeling, analysis, simulation and prediction for biological, engineering, physical and quantum systems; probability theory and
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for remote sensing and uncertainty estimation. Candidates must have a strong programming background. Requirements: PhD in Computer Science or a related field with a strong emphasis on machine learning
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: Machine learning/deep learning model development for biomolecular data analyses and prediction Research Area: Data science and computational chemistry Required Skills: A Ph.D. in relevant field within
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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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. Candidates should either hold a PhD in Computer Science, Information Technology, or a closely related field OR hold a PhD in any field in combination with strong computer programming and data visualization
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The idea is to combine established iterative ensemble Kalman methods with novel emerging machine-learning-enabled model calibration techniques recently adopted in CLM-FATES at UiO. The aim is: to constrain
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transportation operations and network modelling, accessibility analysis, data analysis (statistics and/or machine learning methods), and spatial mapping. Because the work will involve multiple years of daily
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science, medical statistics or machine learning methods Advanced knowledge of electronic healthcare records and their use in development and validation of risk prediction models Knowledge in application
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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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. Qualifications • PhD Degree in a relevant discipline, e.g. electrical / electronic engineering, computer engineering, computer science, etc. • Full experience in computer graphics and robotics area