The Department of Mathematics and Statistics at the University of Saskatchewan invites applications for a one-year postdoctoral position. The faculty mentors will be Dr. Nathaniel Osgood and Dr. Juxin Liu.

The successful candidate will work on innovative computational statistical/Machine Learning methods for the analysis of high-dimensional, longitudinal data related to opioid use and abuse, and health harms, including data drawn from less traditional sources such as text from social media, notes in electronic medical records, and web scraping; web search volumes time series; and compound-specific concentration indicators from municipal wastewater treatment. Some of this analysis is expected to involve combination of such methods with dynamic models, including with Sequential Monte Carlo and Particle Markov Chain Monte Carlo (PMCMC) approaches. This work will be conducted in close collaboration with the Computational Epidemiology and Public Health Informatics Laboratory in the Department of Computer Science, and is supported by the Saskatchewan Centre for Patient Oriented Research and a grant from the Saskatchewan Ministry of Justice, Corrections and Policing.

Applicants must have -- or be close to completion of -- a PhD in statistics or another related field. The successful candidate will also, if eligible, be nominated for a PIMS postdoctoral fellowship (see https://www.pims.math.ca/scientific/postdoctoral), which can be held concurrently.

Applicants should submit a curriculum vitae, publication list, research statement and at least two confidential letters of reference. 

Review of applications will begin immediately; however, the competition will remain open until the position is filled. All applications are to be submitted through MathJobs (https://www.mathjobs.org/jobs/fellowship/15194). 

Any questions regarding this position should be sent to liu@math.usask.ca.

Review of applications will begin immediately and continue until the position is filled. The start date is negotiable but preferably January 1, 2020. This is a one-year position with possibility for renewal.