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credentials. Master’s degree, or equivalent, in statistics or a closely related field with a documented competence in statistical theory and methods. Such competence can be documented by graduate-level
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probability theory or PDE theory to the level of a Master’s degree, and basic familiarity with both. Prior knowledge of specific subdisciplines for the examples listed in the description may be advantageous but
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competence in statistical theory and methods. Such competence can be documented by graduate-level coursework in probability and statistical inference, a statistics-focused Master’s thesis, or relevant
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education in mathematics. The appointed fellow should have expertise in probability theory or PDE theory to the level of a Master’s degree, and basic familiarity with both. Prior knowledge of specific
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measurement quality issues related to respondent non-compliance in ecological momentary assessment or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models
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. The work will be at the interface between data analysis and theory. We are also open to employing data-driven techniques if the candidate wishes. The ocean is currently evolving with the changing climate
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consider all types of data, from full complexity climate models, to turbulence models, to in situ data. The work will be at the interface between data analysis and theory. We are also open to employing data
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using simplified models. But we consider all types of data, from full complexity climate models, to turbulence models, to in situ data. The work will be at the interface between data analysis and theory
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. But we consider all types of data, from full complexity climate models, to turbulence models, to in situ data. The work will be at the interface between data analysis and theory. We are also open to
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or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models in small samples. The appointment is a full-time position and is made for a period of three years