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Econometrics Virtual power plants Power systems and/or power electronics Machine learning Renewable energy systems Advanced statistics Language requirement: Good oral and written communication skills in English
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, we expect machine learning to be employed to improve accuracy and efficiency of numerical methods, combining advanced technology with scientific research. About the Department of Mathematics at UiB
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to complete the final exam. Desired: Familiarity with statistical and machine learning techniques. Knowledge about molecular biology and/or gene regulation. Experience with nanopore sequencing, Hi-C, ribosome
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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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. The HDL and SPKI research groups are part of the Centre of Research-based Innovation SFI Visual Intelligence that is a center-of excellence in machine learning research. The research groups are also active
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an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the following computing skills will be considered an advantage: Natural
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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
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or Machine Learning). The Master’s thesis must be included in the application. Ideal Candidate: Demonstrates experience or strong interest in modelling, programming, systems thinking, and qualitative
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, Mathematics (Operations research) or Computer Science or Machine Learning). The Master’s thesis must be included in the application. Ideal Candidate: Demonstrates experience or strong interest in modelling