Research Technical Assistant AI and Multimodal Foundation Models

Union: Non-Union
Number of vacancies: 1   
New or Replacement Position: New
Site: Toronto General Hospital
Department: Peter Munk Cardiac Centre (PMCC)
Reports to:  Principal Investigator
Salary Range:  $22.60 - $28.25 per hour
Hours: 20 hours per week
Shifts: Days
Status: Temporary Part-time (Approximately 3 months to start)
Closing Date:  September 15 2026

Position Summary

The Peter Munk Cardiac Centre (PMCC) AI team is seeking one highly motivated AI Research Student to join our multidisciplinary team and contribute to the development of next-generation multimodal foundation models and agentic AI systems for biomedical and healthcare applications. This is a unique chance to be at the cutting edge of AI research in healthcare driving projects that make a tangible impact on patient outcomes and clinical practices around the globe. 

Working closely with the Lead AI Scientist staff scientists clinicians and domain experts students will participate in cutting-edge research aimed at building AI systems capable of integrating diverse biological modalities and enabling translational discoveries. This position offers a unique opportunity to work at the intersection of computer vision natural language processing structural biology and biomedical imaging. Successful candidates will have the opportunity to contribute to high-impact research projects publications and open-source software development. This position provides an exceptional opportunity to gain hands-on experience in state-of-the-art AI research and collaborate with leading scientists in a highly interdisciplinary environment.

The successful candidate will join the highly collaborative and exceptionally productive PMCC AI team which brings together clinicians AI and staff scientists software developers machine learning engineers researchers and operational leaders across cardiology cardiac surgery vascular surgery critical care medical imaging and digital health and will help ensure that AI tools are safe auditable scalable and aligned with the strategic objectives of the PMCC and UHN. and aligned with the strategic objectives of the PMCC and UHN. and aligned with the strategic objectives of the PMCC and UHN. For more information about the PMCC AI Team please visit our website at .

Duties  

• Assist in the development and evaluation of foundation models and multimodal AI methods for biomedical and healthcare applications.
• Contribute to the design and implementation of agentic AI systems including single- and multi-agent workflows for reasoning information integration and decision support.
• Work with multimodal biomedical and clinical data with a primary focus on genomics electronic health records clinical text molecular data and other structured and unstructured health data.
• Assist with the development and evaluation of methods for integrating longitudinal clinical and genomic information into unified AI representations.
• Develop test and optimize machine-learning and deep-learning methods using Python PyTorch and related frameworks.
• Participate in data preprocessing representation learning model training benchmarking and evaluation of AI models.
• Contribute to research on foundation-model adaptation agent memory reasoning and multimodal learning for healthcare applications.
• Conduct literature reviews and remain current with developments in foundation models large language models multimodal AI and autonomous/multi-agent AI systems.
• Assist with research experiments analysis of results preparation of figures and interpretation of model performance.
• Contribute to research manuscripts conference submissions presentations technical reports and open-source research software.
• Follow software-engineering and reproducible-research best practices including version control documentation experiment tracking and reproducible computational workflows.
• Collaborate with AI researchers staff scientists computational scientists clinicians and other domain experts on interdisciplinary biomedical research projects.
• Participate actively in research meetings project discussions and regular progress reviews.

Qualifications :

• Currently enrolled in an undergraduate masters or doctoral program in Computer Science Biomedical Engineering Computational Biology Bioinformatics Data Science Artificial Intelligence Statistics Applied Mathematics or a related quantitative discipline.
• Strong programming skills in Python and experience with scientific computing or machine-learning workflows.
• Experience with deep learning frameworks such as PyTorch.
• Familiarity with foundation models large language models multimodal AI or agentic AI frameworks such as LangChain or LangGraph is an asset.
• Solid understanding of machine-learning and deep-learning fundamentals

Preferred Qualifications

• Interest in applying AI methods to biomedical genomic and clinical data.
• Ability to work both independently and collaboratively in an interdisciplinary research environment.
• Ability to manage multiple tasks learn new methods quickly and contribute to a dynamic and translational research setting.
• Familiarity with distributed training and high-performance computing environments such as SLURM will be an asset. 
• Strong analytical problem-solving communication and organizational skills.
• Experience with Linux Git high-performance computing cloud computing or reproducible research workflows is an asset.

Additional Information :

Why join UHN

In addition to working alongside some of the most talented and inspiring healthcare professionals in the world UHN offers a wide range of benefits programs and perks. It is the comprehensiveness of these offerings that makes it a differentiating factor allowing you to find value where it matters most to you now and throughout your career at UHN.

• Competitive offer packages
• Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP access to Transit and UHN shuttle service
• A flexible work environment
• Opportunities for development and promotions within a large organization
• Additional perks (multiple corporate discounts including: travel restaurants parking phone plans auto insurance discounts on-site gyms etc.)

Current UHN employees must have successfully completed their probationary period have a good employee record along with satisfactory attendance in accordance with UHNs attendance management program to be eligible for consideration.

All applications must be submitted before the posting close date.

UHN uses email to communicate with selected candidates.  Please ensure you check your email regularly. At University Health Network (UHN) artificial intelligence technologies may be used to assist in the screening assessment and selection of candidates for this position.

Please be advised that a Criminal Record Check may be required of the successful candidate. Should it be determined that any information provided by a candidate be misleading inaccurate or incorrect UHN reserves the right to discontinue with the consideration of their application.

UHN is an equal opportunity employer committed to an inclusive recruitment process and workplace. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their requirements known.

We thank all applicants for their interest however only those selected for further consideration will be contacted.

Remote Work :

Yes

Employment Type :

Part-time