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access to preventive care and neighborhood characteristics influence long-term health trajectories. The project applies both econometric and machine learning approaches to identify high-risk groups and to
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inference, micro-econometrics, health inequalities, epidemiology, qualitative research methods such as grounded theory, and mixed-methods approaches. Elective courses on data science, public health
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approval, ordering register data, and conducting econometric analysis of large register-based datasets. Further tasks include conducting health economic evaluations, project planning, scientific writing, and
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, initiative, and the capacity to work effectively in a team are essential. Prior experience with econometric software (e.g., Stata, R) and field surveys in developing countries will be considered an asset
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management knowledge into relevant research designs; developing research questions; applying appropriate econometric and qualitative analytical tools; writing scientific manuscripts and compile a Ph.D. thesis