traineeships
INTERNSHIP APPLICATION PORTAL
Applications to the the second cycle of our internship program are now CLOSED. Applications are now under review.
Who are we looking for?
This year we will select interns to participate in our second cohort. Interns will work for 10-15 hours/week for 3-6 months at one of our partner organizations on projects related to AI and public health and equity. Interns will be awarded a $10,000 stipend to support them through their work.
Candidates can apply if they have the following:
- Canadian Citizenship or a valid work permit
- Possess a graduate level degree or are in a graduate trainee program*
- High interest in public health, AI, equity (evaluated through their letter of intent)
- CV with prior research and work experience
*If you are unsure if your education matches the requirements, please reach out to the internship program lead to answer your questions at senthujan.senkaiahliyan@mail.utoronto.ca
If you fulfill the requirements, we welcome you to apply for our internship program this year by filling out the application form below by 15 December 2023.
Incomplete applications will not be reviewed.
When completing the applications, please refer to the discriptions below and only select the top 3 projects you are interested in.
PROJECTS FOR 2023-2024
1. HIVE LAB
Summary: involve harnessing data from various Canadian digital content sources to build and test novel Natural Language Processing models
Preferred Candidate:
- A highly motivated graduate student eager to cultivate robust research portfolio
- Holds a Master’s degree in Computer Science or Health Informatics, with a background in health-related domains, particularly emphasizing machine learning development; other applicants will also be considered.
- Demonstrates intermediate-to-advanced proficiency in Python.
- Enthusiastic about constructing and assessing machine learning models.
- Passionate about the field of Natural Language Processing
2. Pamoja Institute
Summary:
Project 1: measurement and Assessment of Community Resilience: You will be tasked with defining measures and qualitative tools to assess the resilience of communities over time.
Project 2: virtual Agent Development: You will develop a virtual agent that can act as a decision support tool in facilitating resilient community building and resource sharing. The aim is to demonstrate the use of agent-based recommender systems to enhance community resilience and social capital, in a measurable way.
Preferred Candidate:
- Passion for community-centered research and action.
- Strong background in research methodologies
- Proficiency in AI concepts and technologies
- Commitment to anti-oppressive practices and equity
- Collaborative, inclusive, and effective communicator
3. Public Health Agency of Canada
Summary: AI capacity building as part of the Innovative Surveillance Methods team. Intern will support design, logistics & delivery of capacity building events and/or other capacity building products (e.g. literature review, environmental scan).
Preferred Candidate:
- Highly driven graduate student with an interest in AI, public health, engagement, training and events
- Broad background in public health and AI
- Experience with engaging experts, planning seminars, supporting conferences, teaching, literature reviews, environmental scans, or working with public sector teams are all assets.
4. National Collaborating Centre for Methods and Tools (NCCMT), hosted at McMaster University
Summary: explore novel machine learning approaches to handle large quantities of data for literature reviews to support evidence-informed decision making within population and public health.
Preferred Candidate:
- Someone with high interest in population/public health as well as strong technical skills with adapting machine learning models.
- A graduate trainee in computer science or health informatics with machine learning model building experience or an early career professional with significant Machine Learning Operations (MLOps) experience will be considered.
5. Ontario HIV Treatment Network
Summary: fill in the gaps in ARV and other medication regimen data collected through the OCS using machine learning techniques
Preferred Candidate:
- The ideal candidate has strong machine learning skills, particularly experience with natural language processing Strong programming skills, especially in languages like Python and R, are essential, as they will be tasked with developing algorithms to compute medication regimens efficiently.
- The ideal candidate should be a quick learner, adaptable, and possess excellent communication skills to collaborate with statisticians and data engineers on the team effectively. Experience in the HIV sector is not essential, however an interest in learning about working with HIV data and improving health outcomes through health data are preferred.
6. Manitoba’s Data Science Program
Summary: test the feasibility of using synthetic datasets generated from provincial databases to produce useful models and insights for public health analyses. This work will determine the value of this approach and how it can support Manitoba’s commitment to data protection and equity.
Ideal Candidate:
- Advanced graduate training with experience in relevant machine learning approaches such as deep learning, unsupervised learning, and/or generative adversarial neural networks
- Facility with relevant open-source frameworks and advanced proficiency in Python and R
- Keen interest in equity, privacy-preserving methods, and innovation
Strong communication skills
7. 211 Ontario
Summary: the project will use data from interactions with 211 Ontario users (includes controlled and free text values), as well as audio from call recordings to analyze expressed and unexpressed social needs and any emergent patterns
Ideal Candidate:
- Highly driven graduate student with an interest in building a research portfolio
- Prefer candidates who have an understanding of non-profit/human services environment
- Masters in Computer science with a focus on machine learning development, other candidates will also be considered
- Possess intermediate-high level familiarity of Python
- Interested in building and evaluating machine learning models
- Keen interest in Natural Language Processing
8. Simcoe Muskoka District Health Unit
Summary: developing a chatbot that can be used by local public health units (LPHU) for the food safety program in Ontario. The successful intern will have expertise working and fine-tuning open-source large language models to create chatbots that can be deployed LPHAs to provide 24/7 education and management of food safety matters including receiving reports of foodborne illnesses and poor food handling practices. This chatbot will be fitted with an API or external facing platform that can be integrated easily into public health websites and inspection and investigation software infrastructure.
Ideal Candidate:
- Highly driven graduate student (Masters or PhD) with an interest in building a research portfolio
- Significant expertise in foundation large language models
- Committed to solving public health challenges.
- Expert software development skills
The vision of the Artificial Intelligence for Public Health (AI4PH) Health Research Training Platform (HRTP) is to enable skill development and capacity for artificial intelligence (AI) and machine learning (ML)innovations in public health research and practice that have a critical focus on equity and disease prevention. We aim to support training for AI applications that will address health inequities and support learners in developing a critical understanding of AI technologies’ impact on health inequities.
The Artificial Intelligence for Public Health and Health Equity Trainee Scholarship Program is intended to support trainee projects aligned to the goals of the AI4PH HRTP and provide supervision of Masters, PhD, DrPH, and postdoctoral fellows by our named mentors who span disciplinary areas of public health, computer science, biostatistics, equity, policy, and ethics. We aim to empower trainees in both research and applied public health settings with the knowledge to understand the role of AI and the skills to apply AI methods to real public health issues in different contexts.
2023-2024 Application Information
THE APPLICATION PORTAL IS NOW CLOSED. THANK YOU TO ALL THAT APPLIED.
Application Resources
Here is a link to a recording of our May 31st Scholarship Information Session.
DOWNLOAD the Reference Form here: Structured Reference Form
Scholarship application guidance can be found here: Guidance for Scholarship Application
EDI and Community Engagement resources here: EDI/CE Resources (should you have difficulty opening any of the links, please try an alternative browser).
If you would prefer to review this entire page and application form in French, please email ai4ph.dlsph@utoronto.ca.
Eligibility
AI4PH is strongly committed to equity and diversity and encourages applications from racialized persons, persons of colour, women, Indigenous Peoples, persons living with disabilities, LGBTQ2S+ persons, and others who may contribute to the further diversification of scholarship in the area of AI and public health.
Academic Status:
Candidates must be in first, second, or third year (if applicable) of their program/ fellowship at the time of submission.
- PhD, DrPH or MSc candidates must be registered at a Canadian institution in a full-time graduate program for the duration of the scholarship (September, 2023 to May, 2024).
- Postdoctoral candidates must have completed all PhD degree requirements and registered as a postdoctoral trainee by September, 2023.
Research:
Candidates must have a strong record of research and academic excellence commensurate with career stage.
The candidate’s proposed project should clearly demonstrate:
- Scientific rigour and clearly articulated research skills and assets
- Alignment with the mission of the AI4PH Training Platform, including Relevance to public health systems/public health system partners and strong equity considerations
EDI and Community Engagement:
After consultation with our Community Advisory Board, questions have been added to the application to capture engagement with people with lived or living experience (PWLE). Applicants need to:
- Describe their commitment to equity, diversity, accessibility and inclusion in their academic or research work.
- Articulate potential challenges in engaging people with lived experience in their research (e.g. design, data collection, dissemination, etc.).
- Describe the actions planned to overcome these challenges.
- Resources to help answer these questions can be found on our website ai4ph-hrtp.ca under traineeships
Supervision:
Candidates must be supervised or co-supervised by an AI4PH mentor. We encourage co-supervision or committee members from a complementary discipline covering AI, public health, equity and ethics.
The Supervisor(s) should:
- Have an area of expertise that aligns with the trainee’s proposed research and the goals of the AI4PH HRTP.
- Have a clear plan to integrate the trainee into their existing professional and academic networks
- Be based and can hold funds at a Canadian academic institution and permitted to supervise a trainee.
Value & Duration
The AI4PH review committee will adjudicate applicants on an annual cycle. Each year they will offer scholarship support at the Masters’s, doctoral and postdoctoral level. There are two possible funding levels for Master’s and Doctoral students, as indicated below. The full stipend is for those who do not currently hold a major tri-council (i.e. NSERC, CIHR, SSHRC) graduate award. For successful applicants that hold a major award, a top-up stipend will be awarded instead of the full amount. The postdoctoral award is a top-up only stipend awarded at one level. For doctoral and postdoctoral awardees, there is an opportunity to apply to renew funding for up to 3 years.
Funding period: 1 year starting in the Fall
Amount:
Postdoctoral top-up stipend: 20,000 CAD
Doctoral (PhD and DrPH): 20,000 CAD (full) or 9,000 CAD (top-up)
Masters (MSc or MPH): 15,000 CAD (full) or 6,000 CAD (top-up)
Expectations & Deliverables
AI4PH HRTP community participation
- Engaging with faculty members and other trainees through AI4PH events
- Invitation to present at the annual capacity-building workshop and webinars offered throughout the year
- Join and participate in the AI4PH Slack channel
Acknowledge AI4PH-HRTP funding in all related publications and presentations
Submit a final report summarizing trainee research and provide metrics on products that were created during the scholarship funding period (e.g., publications, presentations, etc.)
Commit to becoming an AI4PH alum and engage in alumni activities, including mentorship and networking with future funded trainees
Evaluation Criteria
⇒Quality of the research proposal and public health impact
⇒Alignment with the AI4PH HRTP goals
⇒Quality of the training environment
⇒Commitment to equity, diversity, accessibility, and inclusion
⇒Perspectives on engaging people with lived or living experience
FAQ
Can I apply if I am working on a group project/can multiple people who are working on the same project apply?
⇒ You need to have your own project for this scholarship. Your project may be part of a larger undertaking, but your own individual work needs to be apparent in your application.
Can International students apply?
⇒ International students can apply if they are registered at a Canadian university.
Can MD students apply?
⇒At this time, only Masters, doctoral, and postdoctoral applicants are accepted. Medical student applicants will not be considered.
Do you have to have publications prior to application?
⇒ No. If your application is accepted, any future publications based on work conducted during this scholarship should acknowledge AI4PH-HRTP funding.
Do applicant projects have to clearly align with the expertise or research program of an AI4PH mentor?
⇒ Yes. Information about our AI4PH mentors can be found halfway down this page: https://ai4ph-hrtp.ca/about/
Can you apply if you are only in the starting phase of a project?
⇒ Yes!
How many applicants will be selected?
⇒ We currently have funding for 10 scholars per year.
Are 4th year PhD students/candidates eligible?
⇒ At this time, no. Only 1st, 2nd, or 3rd year applicants (at the time of their submission) are eligible.
Are applicants who come from other fields (for example communications or media programs) eligible?
⇒ Any applicants who are in a Masters/ doctoral/ postdoctoral program are eligible.
Do succesful applicants have to work with an AI4PH mentor?
⇒ Yes. Successful applicants must work with an AI4PH mentor. If you have a current supervisor, we encourage co-supervision with one of our AI4PH mentors
When will the final list of those who got the scholarships be released?
⇒ Applicants will be notified of the results of the review process in August.
Do we need references/reference letters for this application?
⇒ Yes – 2 reference letters are required. There is further guidance on references in the application form.
Can one of my references be an AI4PH mentor?
⇒ If a reference is a mentor, and NOT your supervisor/co-supervisor, their letter will be accepted. We require referees that DO NOT include your supervisor/co-supervisors.
Can I apply for multiple funding streams (Doctoral & Masters, for example)?
⇒ No – please only apply for one type of award. Pick the award that best applies to your degree program.
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