68 parallel-computing-numerical-methods-"DTU" Fellowship positions at University of Oslo in Norway
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knowledge of IRT models, a basic understanding of common estimation methods, and strong programming skills in R, Python, or another relevant computing language. Experience with machine learning methods is a
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calculations. The focus of the project is to perform lifetimes measurements of excited states ranging from few picoseconds to several microseconds via recoil distance Doppler shift (RDDS) and fast timing methods
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with methods for causal inference Familiarity with administrative register data or other types of big data Familiarity with Stata, R, or other relevant computing languages Personal skills A collaborative
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Cookie-erklæringen var sist oppdatert 14.06.2025 Hva er en cookie? En cookie er en liten datafil som lagres på datamaskinen, nettbrettet eller mobiltelefonen din. En cookie er ikke et program som kan
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Cookie-erklæringen var sist oppdatert 30.05.2025 Hva er en cookie? En cookie er en liten datafil som lagres på datamaskinen, nettbrettet eller mobiltelefonen din. En cookie er ikke et program som kan
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of the employment period. Experience in experimental and computational mass spectrometry methods is an advantage. Experience in the preparation of bulk and single-cell BCR libraries is an advantage. Molecular biology
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: Prior experience with analysis of observational remote sensing data sets and/or numerical model output related to cloud properties is desirable. Strong computational skills, and ideally experience with
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The idea is to combine established iterative ensemble Kalman methods with novel emerging machine-learning-enabled model calibration techniques recently adopted in CLM-FATES at UiO. The aim is: to constrain