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Econometrics and Business Statistics at Monash University is globally recognised for its excellence in research and teaching. Our department is a leader in developing cutting-edge methodologies in econometrics
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Location: Stanford, USA; Heidelberg, Germany; or remote The team led by Pascal Geldsetzer at Stanford University is looking for a talented researcher with experience in econometric/quasi
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of Ecosystem Restoration (2021-2030); A good understanding of micro-economic theory, welfare economics and econometric methods. Strong background in applied micro-econometrics; Experience applying econometric
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Qualified candidates must have recently received their Ph.D./ABD in Finance, Statistics or Econometrics Genuinely interested in research and capable of executing research projects with little supervision Have
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Public Policy, providing cutting-edge research in areas such as econometrics, macroeconomics, data analysis, and quantitative methods. Our ideal candidate is comfortable in working independently with a
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dynamics, bubble formations, and trader behavior. Using quantitative methods, econometrics, and statistics, we aim for innovative insights into asset market mechanics. In this role, you'll manage research
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engineering science, with knowledge and/or some experience of energy technology and policy; and/or quantitative analysis including econometrics, statistics and machine learning and related disciplines handling
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engineering science, with knowledge and/or some experience of energy technology and policy; and/or quantitative analysis including econometrics, statistics and machine learning and related disciplines handling
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identifying and reviewing relevant academic and policy literature; sourcing and collating data; undertaking econometric analyses; writing up manuscripts for academic publication; and engaging with a wide range
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, statistical and/or econometric analysis, and developing non-randomised study designs for the evaluation of care technologies or services. ● Write up research methods and findings within reports