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Demonstrated experience in statistical analysis of biomedical or clinical datasets Strong programming skills in R and/or Python Experience in data cleaning, management, and integration from multiple sources
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exposures and human health, e.g. distributed lag nonlinear models, spatial Bayesian methods, case time series, case crossover; have experience with the management and analysis of large climate and/or health
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discussions related to emerging exposure assessment approaches. Cohort-Based Exposome Research Support the analysis and interpretation of environmental exposure data within mother–child cohort studies
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for a technician who will help with the quantitative analysis of a European travel survey and apply data science methodologies to predict travel behaviour in European cities as part of the EC funded
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on the in utero period. The candidate will be responsible of the data management and statistical analysis and will be supervised by Dr. Vrijheid and Dr. Bustamante. KEY RESPONSIBILITIES Data preparation
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Bayesian methods, case time series, case crossover; have experience with the management and analysis of large climate and/or health databases; have experience with Linux environment and scripting; have
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models, spatial Bayesian methods, case time series, case crossover. Have experience with the management and analysis of large climate and/or health databases. Have experience with Linux environment and
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interrelationship with external factors. The candidate will develop the laboratory tasks and fieldwork of the project. In particular, the candidate will be involved in the monitoring and analysis of chemical and