PhD opportunity PHAC and UoG 2027

Using risk models to estimate Canadians’ exposure to antimicrobial resistance with a focus on ESBLs and Modelling/AI Hub support in Risk Assessment Modelling

Funded by Genomics Research and Development Initiative Shared Priority Project (GRDI SPP) GENBIO, and managed by the Public Health Agency of Canada (PHAC)

Project background:

Risk sciences can be used to advance understanding of antimicrobial resistance (AMR) sources, pathways of transmission, and risk to human, animal and environmental health. Traditional risk analysis approaches are well-suited to addressing specific questions, but not to considering the full complex system of AMR sources, pathways and risk factors. The Public Health Agency of Canada (PHAC) has been developing, in close collaboration with federal and academic partners, various tools to assess exposure of humans to AMR hazards and identify effective interventions to mitigate risks. Integrated assessment modelling (IAM) offers a structured approach for organising and processing evidence and uncertainty of complex systems into easily interpretable information to aid policy-making, decisions regarding AMR interventions, interpretation of surveillance data in a broader context, and identification of key knowledge gaps. Both traditional risk analysis approaches and IAMs benefit from genomic data unlocking knowledge previously limited by phenotypic methods.

The objective of this project is to refine and expand existing risk modelling products by incorporating retrospective and prospective genomic data (i.e. genomes) about extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli) and elements of the broader AMR system including the environment, aquaculture, the community, non-enteric bacteria, and imported food.

Study Plan

This project will leverage an existing framework for IAM to assess public health risk and determine appropriate risk management strategies for AMR with a primary focus on ESBL-producing E. coli. This framework will be used to develop models for individual or groups of microbe-resistance-host combinations (e.g., E. coli-ESBL-pigs), where users will be able to explore different scenarios involving reduction or elimination of risk factors, and/or increased use of protective factors. New exposure scenarios and data produced by other work packages in GRDI-SPP-GENBIO project will be evaluated using the IAM.

Additionally, we will develop new risk tools to leverage retrospective sequencing data generated by the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) and other federal partners, as well as prospective data generated throughout the GRDI-SPP-GENBIO project. Specifically, we will develop a Canada-focused Joint Interagency Antimicrobial Consumption and Resistance Analysis (JIACRA)-like model for ESBLs, which is an integrated surveillance approach to analyze relationships between antimicrobial consumption and development of AMR in both humans and food-producing animals. We will also develop a source attribution model using retrospective and prospective data on ESBLs produced by CIPARS, previous GRDI projects, and other GRDI-SPP-GENBIO work packages.

We will establish regular communication with each sub-work package in the project to ensure understanding of project outputs. We will also work on adaptation of genomic/metagenomic data to risk analysis through ongoing integration with national and international collaborators working on relevant methods development.

We are seeking a strong, analytic PhD student to work with key team members at the University of Guelph and the Public Health Agency of Canada, to develop new risk analysis tools including IAM, JIACRA, and Source Attribution products that incorporate genomic data specific to ESBL-producing E. coli. Funding is available for 4 years (starting at $33,000 CAD/year) and the anticipated start date is May 2027.

Qualifications:

Preferred candidates will be able to demonstrate:

• a strong background in statistics and/or bioinformatics and experience using software such as R and/or Python

• experience in risk modelling/simulation and knowledge of risk assessment principles

• experience leading projects and coordinating research

• completion of an MSc in a related field

• strong written and oral communications skills

Priority will be given to Canadian citizens and permanent residents.

Application Process:

Applications will be accepted until 11:59pm on November 30, 2026, or until the position is filled. Interested applicants should submit:

• a cover letter indicating their interest in the project and describing their relevant experience

• unofficial transcript(s)

• full curriculum vitae (CV)

• contact information for two references

Please submit the above materials as a single PDF file to Dr Jane Parmley, Department of Population Medicine, University of Guelph (jparmley@uoguelph.ca).