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measurements are most informative and guiding where, when and how to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more
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to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more efficient, intelligent, and impactful. You will integrate field
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that allow environmental observing systems to adapt and learn from data - identifying which measurements are most informative and guiding where, when and how to observe next. By combining Bayesian inference
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about the users and their activity on the website. The Information is used to track and analyze user behavior, to meet the individual user needs and to deliver targeted advertising. Personvernregler