As seen during the COVID-19 pandemic, population behavioural reaction to the current state of disease prevalence, and how it is being portrayed in the media, can have a large effect on the transmission dynamics of a disease at any given point in time. Caitlin Ward, who will complete her PhD this Spring, is aiming to produce models that better mimic the dynamics of how a disease spreads through a population to improve forecasting and to better understand the drivers of disease transmission. As a recipient of the CANSSI Distinguished Postdoctoral Fellowship, Caitlin will be starting this project later this year under the supervision of Rob Deardon from the University of Calgary and Alexandra M. Schmidt from McGill University.
“I chose to do the CANSSI Distinguished Postdoctoral Fellowships project with Dr. Deardon and Dr. Schmidt because the topic is closely aligned with my current research and the fellowship provides me with excellent opportunities to teach and engage in professional development activities to help advance my career,” says Caitlin. “I’m very excited to work with experts in my field on exciting research and to experience life in Canada.”
Caitlin Ward received her BSc in statistics from Iowa State University before studying biostatistics at the University of Iowa, where she received her MSc and will complete her PhD this spring. Her research has focused on developing methods for hierarchical Bayesian models, with an emphasis on infectious disease modeling.
About the Supervisors
Rob Deardon is a Professor of Biostatistics with a joint position in the Faculty of Veterinary Medicine and the Department of Mathematics and Statistics at the University of Calgary. Much of his recent work has been in the area of infectious disease modelling and surveillance, and Bayesian and computational statistics. Rob is also interested in experimental design, spatio-temporal modelling, statistical learning, and statistical modelling in general.
Alexandra M. Schmidt is a Professor of Biostatistics and the University Chair in the Department of Epidemiology, Biostatistics and Occupational Health at McGill University. She is a Fellow of the American Statistical Association and was awarded the 2017 Distinguished Achievement Medal of the American Statistical Association’s Section on Statistics and the Environment. She is a Bayesian statistician working on the development of flexible spatial and spatio-temporal models for environmental, ecological, and infectious disease problems.
CANSSI’s Distinguished Postdoctoral Fellowships
This program provides a comprehensive training experience to prepare postdoctoral fellows for success in a variety of careers. The CANSSI Distinguished Postdoctoral Fellowship will include a substantial research project in statistics or inferential data science, a substantial interdisciplinary or applied collaboration/interaction, teaching experience, broadly defined, equivalent to 1-2 courses total over two years, and opportunities for professional development. This two-year fellowship is supported by a competitive salary.