General DescriptionBayesian modelling for child mortality Applications are being sought for a 10-Â-12 month full-Â-time position with the Maternal Child Epidemiology Estimation (MCEE) team. Purpose Background At the same time, MCEE work has revealed gaps and methodological challenges that need to be addressed to improve the reliability and accuracy of MCEE's cause-Â-of-Â-death estimates. The core of MCEE's mortality estimation approach involves using multinomial models to predict cause of death distributions. The current project involves shifting these models from a frequentist statistical framework to a Bayesian framework, to facilitate the incorporation of country-Â-specific random effects into the model, and to improve model selection. This work has the promise of being both useful and intellectually stimulating. Work to be performed Timeline
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QualificationsCandidates should have an advanced degree in Computer Science, Statistics, Biostatistics, or similar quantitative fields. The candidate should have strong computational skills and knowledge of statistical modelling. Expertise in writing code for Bayesian analyses, preferably using R, is essential. Experience with JAGS, STAN, or similar programs is strongly preferred. Application InstructionsInterested candidates should email a cover letter and CV to jperin@jhu.edu. Applications will be reviewed until the position is filled. If you have questions about this position, please contact Jamie Perin(jperin@jhu.edu). |
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