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Position: Postdoctoral Fellow in Biostatistics
Institution: University of Oslo
Location: Oslo, Østlandet, Norway
Duties: The post holder will carry out research in statistical methodology related to analysis of high-dimensional data and apply this to analysis of studies in nutrition with the aim of understanding inter-individual variation in cardiometabolic responses to dietary interventions. From a methodological point of view, we are specifically interested in variable selection with error control in high-dimensional linear mixed models, while understanding inter-individual variation in response to dietary interventions is a prerequisite for developing personalized nutritional guidelines. The work will be carried out in close collaboration with researchers at both the Department of Biostatistics and the Department of Nutrition
Requirements: Applicants must hold a PhD degree in statistics, biostatistics, mathematics, or other relevant discipline, with documented experience in statistics; Some knowledge and experience with high-dimensional statistics (e.g. penalized regression models) is an advantage; Experience with genomic data is an advantage, but not necessary; Documented programming skills in R, python, MatLab, C, C++ or equivalent are necessary
   
Text: Postdoctoral Fellow in Biostatistics The post holder will carry out research in statistical methodology related to analysis of high-dimensional data and apply this to analysis of studies in nutrition with the aim of understanding inter-individual variation in cardiometabolic responses to dietary interventions. From a methodological point of view, we are specifically interested in variable selection with error control in high-dimensional linear mixed models, while understanding inter-individual variation in response to dietary interventions is a prerequisite for developing personalized nutritional guidelines. The work will be carried out in close collaboration with researchers at both the Department of Biostatistics and the Department of Nutrition Applicants must hold a PhD degree in statistics, biostatistics, mathematics, or other relevant discipline, with documented experience in statistics; Some knowledge and experience with high-dimensional statistics (e.g. penalized regression models) is an advantage; Experience with genomic data is an advantage, but not necessary; Documented programming skills in R, python, MatLab, C, C++ or equivalent are necessary
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