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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
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/quantitative research methods Documented programming experience for example GitHub project on MATLAB, Python, Julia, Javascript Possesses a strong academic record, with relevant experience in either industry
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, programming, systems thinking, and qualitative/quantitative research methods. Documented programming experience for example GitHub project on MATLAB, Python, Julia, Javascript. Experience in mathematical
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the theories and methods intended to be used. The project proposal plays an important role in evaluating applicants and must demonstrate how the project will lead to the successful completion of a doctoral
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-FATES model using: Snow cover Flux tower data The idea is to combine established iterative ensemble Kalman methods with novel emerging machine-learning-enabled model calibration techniques recently