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Screen reader users may encounter difficulty with this site. For assistance with applying, please contact hr-accessibleapplication@osu.edu . If you have questions while submitting an application
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secondary datasets). Apply advanced analytical techniques (e.g., econometrics models; AI tools; MCDA; cognitive mapping) to generate robust, actionable insights. Design innovative financing channels and
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Proficiency in relevant research methodologies (advanced statistical and econometric data analysis) Ability to work both independently and within international teams Application Requirements Curriculum Vitae
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diverse data sets, applying advanced analytics, and leveraging ML/AI techniques to detect, quantify, and forecast global risks affecting sourcing strategies. It will also include assessing AI-driven demand
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subfields will also be given full consideration. Advanced methodological training is essential; this includes high-level familiarity with causal inference, experimental methods, and econometric techniques
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-level familiarity with causal inference, experimental methods, and econometric techniques. Familiarity with public opinion research and experience working with historical sources would be helpful, but not
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agricultural economics, economics, statistics, or related fields (with emphasis in applied econometrics) by the time of appointment. Candidates will be evaluated on: Proficiency in Excel; demonstrated experience
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; this includes high-level familiarity with causal inference, experimental methods, and econometric techniques. Familiarity with public opinion research and experience working with historical sources would be
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show evidence of understanding, expression and application of concepts and methods. Strong data analysis skills, especially in applied econometrics and statistical methods within health economics are
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skills, especially in applied econometrics and statistical methods within health economics are essential as is the ability to work effectively independently and collaboratively. Diversity Committed