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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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positions within their disciplines. A career plan shall be developed for the Postdoctoral Fellow, specifying the competencies the Postdoctoral Fellow should acquire. UiO is responsible for following up
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related field. Documented expertise in machine learning and time-series modelling (e.g. LSTM, XGBoost, CNN). Strong programming skills in languages such as Python and R. Experience with phenotyping data
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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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Fellow should acquire. UiO is responsible for following up on the career plan and ensuring that the Postdoctoral Fellow has access to career guidance throughout the postdoctoral term. If the Postdoctoral
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30 Sep 2025 Job Information Organisation/Company University of Bergen Department Centre for the Science of Learning & Technology Research Field Educational sciences » Education Educational sciences
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/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines for plausible narratives of regional climate change, novel algorithms for rare
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challenge. This project aims to explore data-driven Artificial Intelligence/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines
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challenge. This project aims to explore data-driven Artificial Intelligence/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines