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comprehensive databases combining nationwide Norwegian health and socioeconomic registry data, biobanks and patient-reported data. Using advanced epidemiological methods, causal inference and machine learning
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epidemiological methods, causal inference and machine learning techniques, we aim to: Improve understanding of risk factors for primary headaches Predict diagnosis and disease progression Identify the most
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the application of rock physics models, Bayesian inversion methods, and machine learning algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or
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inference methods, survey design, and/or machine learning Experience with web scraping and API-based data collection Organizational and coordination skills, such as assisting in drafting terms of reference
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will be adapted to the candidate’s background and the evolving needs of the center. Possible directions include the application of rock physics models, Bayesian inversion methods, and machine learning
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ethnomycology or ethnobiology large-scale (ethnographic) database construction phylogenetic comparative analyses with Bayesian computational tools The applicant must have the ability to work independently and in