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graduate-level knowledge of spatial analysis, machine learning, large dataset management, and statistics or econometrics. Applicants must be proficient in R and/or Python. Advanced knowledge of R's and/or
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financial services. For more information about EPAR, please see: https://epar.evans.uw.edu/ This position is a combination of service and applied research and may include preparing confidential reports
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values rest on credibility, trust and security. By having the courage to think freely and innovate, our actions together, large and small, contribute to a better world. We look forward to receiving your
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6 Jul 2026 Job Information Organisation/Company Wageningen University & Research Research Field Agricultural sciences » Agronomics Agricultural sciences » Soil science Economics » Agricultural
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) Cleaning and managing large datasets from administrative data sources or online learning platforms Causal machine learning (e.g., double/debiased machine learning (DML), causal forests, generic ML) Learning
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health more generally. Data sources for our work in this area are large-scale electronic health record data, medical claims data, mortality registries, and epidemiological cohort studies. The researcher