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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
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-scale assessment data, meta-analyses of meta-analyses) Methods and approaches to cumulative, living, and community-augmented meta-analyses Methods and approaches to include machine learning and artificial
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, and AI chatbot chats; (b) quantitative content analysis; (c)text mining and machine learning methods; (d) survey design and public opinion research; (e) election studies; (f) the Norwegian political
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economics of ICTs / AI. Experience with one or more of the following empirical research methods will be considered an advantage: applied microeconometrics and causal inference; machine learning and data
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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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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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while maintaining energy production efficiency. The integration of machine learning (ML) in predictive maintenance has transformed hydroelectric operations by enabling data-driven decision-making and real
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, mathematics (Operations research) or Computer Science or Machine Learning) the master thesis must be included in the application Ideal Candidate: demonstrates experience or strong interest in modelling
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at https://cbu.w.uib.no/joshi-group/ . Co-supervisors include experts in machine learning and AI, Pekka Parviainen and Tom Michoel, alongside leading epidemiologists, Tone Bjørge and Kari Klungsøyr. The core
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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