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or soon after Advanced training in econometrics, empirical archival methods, and causal inference methods Strong programming skills in Stata, SAS, R, Python, or similar software Experience in teaching
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methods, and econometric models; and 3) contributions to reports, presentations, and peer-reviewed journal articles. The successful candidate will have the opportunity to collaborate with ORNL scientists
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of various forms. The majority of research will be conducted in Stata. Preferred Qualifications Work Experience: Experience with applied causal inference and econometric design Experience with applied
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the position, preferably with a focus on health-related issues.- Demonstrated training or experience with using econometric methods (e.g., differences-in-difference, regression discontinuity, instrumental
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. Expertise in metals and materials markets, energy technology manufacturing, or supply chains. Proficiency in economic analysis techniques such as econometrics, input-output models, and cost modeling
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able to further develop your skills in econometrics and quantitative as well as qualitative methods (e.g., surveys and interviews). Have a basic working knowledge of the Dutch language, because the data
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a PhD in agricultural and resource economics, economics, or related field by the start of the position. The ideal candidate has a strong quantitative background (econometrics and causal inference
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(community interventions, community-based participatory research, meta-analysis and bias in research, RCT methods, causal interference, mathematical modeling, and econometrics) Policy research related
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a deep theoretical understanding of AI, practical proficiency in using AI will be considered in the selection process. A background in causal inference using econometric methods that can be used
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, survey testing, data quality monitoring, and more. Conduct econometric analysis under the direction of senior researchers. Manage relationships with collaborating institutions, including data collection