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researchers at the Chair of Econometrics and Statistics esp. in the Transport Sector and together with the other universities and chairs being part of the CRC. General Requirements: We are looking for first
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knowledge of quantitative methods, particularly in statistics and econometrics; experience in machine learning is a plus Background in business/management/behavioral science Experience with programming
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and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) A high motivation and the ability to work independently with a strong team
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disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with
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a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation
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: TRR408-A7 Investigators: Prof. Dr. Ostap Okhrin, Chair of Econometrics and Statistics esp. in the Transport Sector and co-supervised by Prof. Dr. Kai Nagel, Chair of Transportation System
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German Institute for Economic Research (DIW Berlin) • | Berlin, Berlin | Germany | about 17 hours ago
English Languages English Full-time / part-time full-time Programme duration 8 semesters Beginning Winter semester Application deadline Middle of January for the following winter semester starting on 1
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Your Job: Maintain, and update quantitative methods for assessing economic impacts of the energy transition at the national and regional levels Develop dynamic and multisectoral economic models
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module I: Basics in quantitative and qualitative methods Compulsory module II: Statistics and econometrics or Advanced methods in qualitative research Compulsory module III: The sociological and economic
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Languages The general working language in the Berlin School of Economics is English. All courses are held in English. Full-time / part-time full-time Programme duration 8 semesters Beginning Winter semester