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Postdoc in modelling Greenland and Himalaya precipitation using machine learning Faculty: Faculty of Science Department: Department of Physics Hours per week: 36 to 40 Application deadline: 26
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: A PhD in Computer Science, Engineering, Mathematics, theoretical Physics or other degree programs from top universities involving at least one of the following topics: Machine Learning, AI, Dynamic
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: A PhD in Computer Science, Engineering, Mathematics, theoretical Physics or other degree programs from top universities involving at least one of the following topics: Machine Learning, AI, Dynamic
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Centrum Wiskunde & Informatica (CWI) has a vacancy in the Machine Learning research group for a talented Postdoc/researcher (m/f/x). Job description We are looking for a motivated postdoctoral
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applications* in close collaboration with other discipline experts (software, microelectronics and applications engineers). * except for RF payloads. ** including artificial intelligence and machine learning
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records from satellite data, and/or improved methods of uncertainty characterisation, including the use of artificial intelligence and machine learning to improve or analyse satellite climate data records
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on methods such as functional connectivity analysis, brain network analysis, or machine learning; Excellent scientific writing and communication skills in English; Ability to work independently while
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, ballistocardiography, and bio-radar) in combination with machine learning based algorithms for time series analysis into the whole OSA diagnosis and treatment pathway. During diagnosis unobtrusive sensors that can be
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in combination with other machine learning techniques, to create predictive models. You will engage in an interactive feedback loop with domain experts to analyze discovered models and remove any
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(UQ) for machine learning and its validation. Your areas of research will be chosen based on both your own expert judgement and insight into trends and developments and on team requirements to ensure