Post-doctoral Fellowship in perinatal predictive modeling, McMaster University, Hamilton, Ontario, Canada
Recent new research funds from a Canadian Institutes of Health Research grant and a Canada Research Chair position have become available for a post-doctoral position at McMaster in the Departments of Obstetrics and Gynecology/Health Research Methods, Evidence, and Impact (HEI, formerly Clinical Epidemiology & Biostatistics), to develop and apply novel, advanced analytic methodology to build, validate and apply novel predictive models of complex biological processes to study maternal and neonatal diseases to improve the health of women and infants. This postdoctoral fellowship will enable fellows to extend knowledge in their research areas, conduct successful interdisciplinary research projects, enhance writing and communication skills and establish new peer networks while aiming to improve the health of women and infants.
The successful candidate will be co-supervised in a vibrant, collaborative environment by Dr. Sarah McDonald, holder of a prestigious Canada Research Chair, a perinatal clinical epidemiologist and a high risk obstetrician and Dr. Joseph Beyene, an academic biostatistician and methodologist. Opportunities include collaborations with other departments, centres, provinces and internationally.
We are seeking highly motivated applicants with a Ph.D. in (Bio)Statistics, Computer Science, Clinical Epidemiology, or related field. Superlative programming (SAS/R) and communication skills are required. The applicant should be able to work as part of a team as well as independently, and be enthusiastic about working with real or simulated large perinatal data sets to tackle the high dimensionality of complex relationships between patient characteristics, biomarkers, & repeated measures to examine maternal and infant outcomes. Experience in obstetrics or neonatology is an asset.
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