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should have a background (MSc, research master) in Economics or Econometrics, preferably with a specialization in international economics, development economics, and/or applied econometrics. Familiarity
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PhD position “Climate Finance: Moral Responsibilities of Financial Institutions for Decarbonization”
, regulation and the public debate. Organisation The PhD position is embedded in the research programme of Economics, Econometrics & Finance of FEB’s Research Institute. The project will be supervised by dr
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economics, economics of education or applied econometrics) or related disciplines. Applicants with quantitative skills and an interest in interdisciplinary research are highly encouraged to apply. Additional
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, economics of education or applied econometrics) or related disciplines. Applicants with quantitative skills and an interest in interdisciplinary research are highly encouraged to apply. Organisation
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interdisciplinary environment. You can effectively communicate research findings to both academic and policy audiences. You also possess: a successfully completed MSc degree in agricultural, environmental or applied
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Management & Strategy. Where to apply Website https://www.academictransfer.com/en/jobs/350186/phd-position-in-the-field-of-or… Requirements Specific Requirements The ideal candidate is ambitious, highly
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Accounting and Auditing of FEB’s Research Institute. The project will be supervised by Jos Offerein, Yasemin Zengin-Karaibrahimoglu and Reggy Hooghiemstra. Where to apply Website https
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that are coherent, reliable, aligned with principles of rationality, while also reflecting the preferences of their principals. Organisation The PhD position is embedded in the Economics, Econometrics, and Finance
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inflows, particularly those leading to substantial foreign control over strategically vital sectors, such as infrastructure, defence, and advanced technology, have raised concerns about national security
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to staff position within a Research Infrastructure? No Offer Description Do you want to contribute to extending, applying, and disseminating flexible methodologies from the Bayesian machine learning