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University of Guelph
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Postdoctoral Fellowship in AI/ML/Quantitative Methods University of Guelph in Canada
Degree Level
Postdoc
Field of study
Computer Science
Funding
Salary range is 60,000 to 65,000 CAD per year, with salary negotiable.
Deadline
Mar 1, 2027
Country
Canada
University
University of Guelph
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About this position
This postdoctoral fellowship at the University of Guelph sits within the Department of Mathematics and Statistics and the broader College of Computational, Mathematical, and Physical Sciences. The project focuses on developing innovative AI/ML- and quantitative-methods-based approaches to address challenges in viral hepatitis infection.
The fellow will work on novel modelling frameworks to estimate the total prevalence of viral hepatitis in Canada, including the undiagnosed proportion of cases, using health administrative data. The research is aimed at improving understanding of viral hepatitis transmission, strengthening epidemic forecasting, and quantifying uncertainty for public health policy and decision making.
The position is embedded in an established interdisciplinary team that brings together mathematical modelers, statisticians, biostatisticians, health services researchers, health economists, physicians, and health policy makers. The successful candidate will collaborate closely with analysts, the principal investigators, and other team members across the project.
The fellowship is co-led by Dr. Zeny Feng at the University of Guelph and Dr. William Wong at the University of Waterloo. The role includes model development and implementation, data collection and data management activities, supporting analyses on related projects, contributing manuscripts for peer-reviewed publication, and helping develop grant applications. Collaboration with other researchers, analysts, and students is also part of the role, with scope to contribute to supervision.
Funding details
Salary range is 60,000 to 65,000 CAD per year, with salary negotiable.
What's required
A PhD in Statistics, Applied Mathematics, Computer Science, or Management Science, or a related field is required, together with a strong background in applying and integrating AI, machine learning, and quantitative methods. Experience working with health administrative data is considered an asset. Proficiency in Python, SAS and/or R is required, along with strong sense of urgency, excellent time management, strong organizational skills, and the ability to meet project goals and deadlines.
How to apply
Prepare a cover letter, CV, summary of research experience, publications, and one or two selected publication reprints or preprints or a summary of research projects. Include the names of two referees and email the application to Dr. Zeny Feng and Dr. William W.L. Wong.
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Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.