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related discipline): Computer Science, Artificial Intelligence, or Machine Learning Economics or Econometrics (particularly applied micro, behavioural, or decision-focused modelling) Applied Mathematics
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mutual agreement, it has the possibility to be extended to a second-year. Responsibilities: • Use advanced econometric methods to analyze large-scale datasets, including claims data • Produce policy
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the energy transition Experience and competency in quantitative analysis, including applied econometrics Experience in applied theoretical modeling a plus Proficient at statistical software, e.g., STATA
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Call for positions of Researcher, Post-doctoral Researcher, Junior Researcher and Research assistant
6 Mar 2026 Job Information Organisation/Company Economics Institute of the Czech Academy of Sciences Department Personnel Office Research Field Economics » Microeconomics Economics » Econometrics
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Dyson School of Applied Economics and Management. The Postdoctoral Associate will contribute to quantifying the private value of improved soil health across the U.S. using econometric techniques and
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, econometrics/causal inference, data management, coding (e.g., in Stata or R), and applied policy-relevant research. Skills in geospatial analysis and/or data visualization would be a plus. The candidate should
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in applied economic analysis (e.g., causal inference, econometrics, spatial equilibrium modeling). • Experience working with large-scale datasets and interdisciplinary research. • Demonstrated research
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– Chair of Banking Regulation (currently under establishment; expected to be launched in mid-2026) Description: A full-time postdoctoral researcher position is offered to carry out applied research
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strong quantitative skills and demonstrated experience in applied econometric analysis, large-scale data integration, and global or regional economic modeling, as well as an interest in climate risk, soil
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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