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-compliance in ecological momentary assessment, or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models in small samples. The ideal candidate has prior
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mathematical modelling tools. Excellent knowledge of programming languages such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in
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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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the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation until 2033. The project PI and team are also in close collaboration
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; machine learning and data science. Experience with one or more of the following computing skills will be considered an advantage: Natural Language Processing and LLMs; R; Python. Applicants must be fluent
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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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studies. Proficiency in relevant computational tools and statistical methods. Experience with machine learning in large datasets. Interest and motivation to work in a multidisciplinary team. Ability to work
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. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in English Desired qualifications: Experience with research on epidemiological modelling, with an emphasis
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the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation until 2033. The project PI and team are also in close collaboration