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are at advanced level in a subject relevant to the call, or otherwise acquired substantially equivalent knowledge. You have good analytical skills, and a strong interest in quantitative research. You have good
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in the labour market change are poorly understood. The main aim of this project is to fill this knowledge gap using quantitative research methods on administrative data from Statistics Netherlands and
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interest in socioeconomic policy issues and social questions. You have a solid background in quantitative research methods and data analysis. You have a good knowledge of statistical software packages
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questions. You have a solid background in quantitative research methods and data analysis. You have a good knowledge of statistical software packages such as STATA, SPSS, SAS or R, or willing to acquire
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research and are motivated to create an impact with your research. You have an affinity with transdisciplinary research. You have demonstrable affinity and experience with quantitative research such as
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of this project is to fill this knowledge gap using quantitative research methods on administrative data from Statistics Netherlands and (experimental) survey data for (European) countries. The position comprises
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University College Dublin, School of Agriculture and Food Science | Dublin Bar, Leinster | Ireland | about 1 month ago
opportunity in the area of upcycled foods. This UCD funded project will focus on co-creating upcycled foods with consumers using a variety of qualitative and quantitative research methods, such as focus groups
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about empirical research and quantitative research methods. You are a team player with good communication skills. The candidate must thrive in a collaborative environment that calls for autonomy
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of population economics Programming skills in STATA or R or any other statistics Software To have a basic understanding of quantitative research methods (data analysis, econometrics) in economics Proficiency in
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immediate leader is Johan Håkon Bjørngaard. Duties of the position Conducting quantitative research using large-scale individual-level registry data Performing instrumental variable, and multivariable