Full time, Toronto, Canada
The Centre for Global Health Research (CGHR – www.cghr.org) is a non-profit and non-partisan organization associated with the University of Toronto and St. Michael’s Hospital. CGHR’s mission is to lead high-quality public health research that advances global health for all, with particular attention to the world’s poorest populations. Its flagship project, the Million Death Study (MDS), is run in collaboration with the Government of India and documents causes of death across the country. The Centre consists of a team of multidisciplinary scientists, researchers, and analysts in fields including Biostatistics, Epidemiology, Machine Learning, and Health Geography.
We are looking for a candidate with a background in Statistics or an allied discipline to engage in both methodological research and applied collaborative research on projects involving spatial and spatio-temporal methods related to Global Health. The applied research projects will be concerned with quantifying changes in mortality worldwide, and identifying exploring spatial variation in these temporal patterns at the sub-national level. The statistical methodology component of the research will involve developing models and methods of inference for large and spatially referenced annual health surveys, which are the primary source of mortality data in low- and middle-income countries. Additional information appears in the research summary.
This is a full-time contract position, starting as soon as possible after December 2017.
This position will involve both collaborative research for publication in top-ranked scientific journals and methodological research leading on one or more substantive methodological problems to be published in the Statistics literature. The successful candidate will act as lead author for the methods work, with Dr. Patrick Brown (who is cross-appointed to the Department of Statistical Sciences at the University of Toronto) as collaborator and academic supervisor. Methods to be considered include multivariate age-period-cohort models, geostatistical models, and approximate inference for non-Gaussian high-dimensional hierarchical models. It is intended for the methods developed to be implemented and released in an R package.
The collaborative portion of the position will involve working in an interdisciplinary research team, providing input on statistical issues and carrying out non-standard and complex analyses. The role will require strong computer skills for writing clean and legible R code for carrying out statistical analyses which are well-presented and fully reproducible. Demonstrated ability to be an enthusiastic and self-motivated learner, work well independently and within a team, and be a critical thinker is essential to this position. The successful candidate will gain valuable experience in a growing, high-impact research area while contributing to the improving health of the global population.
See the research summary here
Please send a cover letter, two-page research statement (see research summary), and CV with references to: email@example.com. Please quote “Postdoctoral researcher in Geostatistics and Global Mortality” in the subject line. To discuss the position further, contact Patrick Brown at firstname.lastname@example.org.
Deadline for applications: Open until filled