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required Strong training in economics, econometrics, and data science, with a demonstrated potential for excellence in research and teaching Priority will be given to candidates who have prior experience
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required Strong training in economics, econometrics, and data science, with a demonstrated potential for excellence in research and teaching Priority will be given to candidates who have prior experience
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. Occupational Summary The Department of Neurology seeks a Post-Doctoral Fellow to work in the Vascular Neurology division on clinical research at the interface of causal inference, econometrics, biostatistics
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econometric time series analysis, focus group discussions, and a choice experiment. Hence, we seek a candidate having expertise with some of these methods, and interest and capacity to learn the others. It is
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understanding of decentralised markets and blockchain-based financial systems. Relevant areas include market microstructure, asset pricing, financial econometrics, risk management, macroeconomics and tokenomics
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understanding of decentralised markets and blockchain-based financial systems. Relevant areas include market microstructure, asset pricing, financial econometrics, risk management, macroeconomics and tokenomics
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, econometric, and other methods to strengthen causal inference using multilevel, longitudinal data and quasi-experimental approaches, along with the exploration of gender, racial/ethnic and socioeconomic
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 10 hours ago
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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range of methodologies, including econometric analysis, micro-econometric demand analysis, big data analysis, health macroeconomics, discrete choice experiments, cost-effectiveness analysis, decision
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determinants of health with a focus on cognitive decline/dementia and an emphasis on the application of epidemiologic, econometric, and other methods to strengthen causal inference using multilevel, longitudinal