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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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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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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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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