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as well as explainable AI methods to understand disease drivers leading to early disease diagnosis and the discovery of novel digital biomarkers in the context of chronic liver disease for the LIVERAIM
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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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methodology to estimate travel behavior on a large scale in Europe. Main duties and tasks: To conduct quantitative analysis and implement data science methods for transport modelling. The technician will work
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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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elements in contribution to improving health worldwide. Where to apply Website https://jobs.isglobal.org/jobs/7100658-air-and-human-microbiome-studies/50d5608… Requirements Research FieldBiological