Practicum Student – AI-driven respiratory virus forecasting

Practicum Student AI-driven respiratory virus forecasting

Location: Toronto-661 University

Department: Scientist Third Party Grants

This posting is to fill a current vacancy.

Description of the placement:
We are looking for a student interested in infectious disease epidemiology and machine learning methods who is seeking an opportunity to develop their epidemiologic and analytic skills. This project will focus on advancing machine learning methods for short-term (nowcasting) surveillance of SARS-CoV-2 influenza and RSV activity in Ontario. The student will contribute to the development and evaluation of a range of algorithmse.g. Random Forest Extreme Gradient Boosting (XGBoost)using time series cross-validation to assess predictive performance. The project will also explore ensemble forecasting strategies that intelligently combine outputs from multiple models to balance sensitivity and stability. By improving the precision and reliability of respiratory virus forecasts this initiative will enhance public health situational awareness and support timely evidence-informed decisions in outbreak response resource allocation and health system planning.
Working with Scientists and staff from the Communicable Disease Control Communicable Diseases and Data Science and Analytics teams the student will have the opportunity to develop analytic plans and undertake statistical analyses. The student may also contribute to the preparation of a report or manuscript.
This practicum is an ideal fit for a student with strong statistical analysis skills who wishes to gain experience in infectious disease epidemiology. The student will work as part of a multidisciplinary research team to conduct the work and will have the opportunity to learn more about the datasets available at PHO and how they can be used to contribute to public health research.

Suggested placement start date: May to August 2026

Please note:
This position is only open to students who are currently enrolled in an academic program where the completion of a practicum placement/internship is required.
This position is only open to students currently residing in Ontario and attending a Canadian academic institution. Preference will be given to students enrolled in Ontario-based academic institutions.
This is a paid placement.

Educational objectives:

• Develop and apply analytical skills (e.g. machine learning forecasting ensemble models).
• Practice communication skills (i.e. abstract and manuscript writing team presentations).
• Gain experience in public health and working with laboratory testing data.

Proposed deliverables at the end of the placement:

• An abstract for submission to a conference.
• A manuscript for submission to a peer-reviewed journal or report delivered to the team.

Required education and experience:

• Currently enrolled in a Masters degree in biostatistics epidemiology computer science data science or similar where the completion of a practicum/internship placement is required.

• Good knowledge of R for data manipulation and analysis preferred but experience with another analytic software will be considered.
• At least a basic understanding of machine learning and forecasting methods.
• Familiarity with infectious disease epidemiology would be considered an asset.

Duration: Student (Fixed Term) 3 month(s)

Hours of Work: Full time 36.25 hours per week

Compensation Group: Individual Contributor

Compensation Range: $700.00 - $725.00

Posting Date:

Closing Date:

Please note: applications will be received no later than 11:59pm on the date preceding the closing date as indicated on the Job Requisition.

Note: Internal candidates will be considered first.

While we thank all applicants for their interest only those selected to move forward in the recruitment process will be contacted. Any information obtained during the course of recruitment will be used for employment recruitment purposes only and not for any other purpose.

PHO is committed to ensuring equity in employment. Our goal is to create a diverse inclusive workforce that reflects the communities we serve and to ensure our services and communications are accessible to all individuals. Any candidate who requires a job posting in an alternative format may email a request to Once an applicant has been selected for an interview they can inform PHO about any accommodations they may require at any stage of the interview process.