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the project core group. The PhD/postdoctoral research fellow is invited to develop a specific research focus related to the efforts to build novel forms of collaborations and research practices of the life
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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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mapping methods that are better suited for decision-making by raising map quality, practical relevance and applicability. Building on these insights, the project will advance methodologies for ecosystem
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from industry, science, and policy management to co-develop ecosystem mapping methods that are better suited for decision-making by raising map quality, practical relevance and applicability. Building
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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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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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become part of DRESS’ core team which includes PI Ragnhild M. Bø and a PhD. The team benefit from an advisory board of internationally renowned scholars and will also be joined by a research assistant in
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/Chaplaincy (LES). This program focuses on the relationship between theory and practice in religious and worldview leadership and counselling, as well as building competence to relate professionally
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be used to generate new readings of the Timaeus, and related Platonic dialogues. The research team will consist of three post-docs, two PhD students, the PI, and associated international experts
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consist of three post-docs, two PhD students, the PI, and associated international experts. The appointed post-doc will work along the three axes of the project, the early Pythagoreans, the Timaeus, and