Research Student

Union: Non-Union
Number of vacancies:  1
Site: Toronto General Hospital
Department:  Research
Reports to:  Director
Hours: 37.5 hours per week
Shifts: Days
Status: Temporary Full-time
Closing Date: August 29 2025

Position Summary 

In collaboration with teams across University Health Network the AI Hub is working to transform cancer care through PMATCH a project aiming to connect patients to suitable clinical trials in a timely and personalized way. The AI Hub is leveraging large language models to extract discrete data from unstructured clinical text. The AI Hub is excited to announce an opportunity for one student intern to collaborate with our team of AI Scientists Machine Learning Engineers and the greater PMATCH working group to advance the use of Natural Language Processing in healthcare. 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. The role offers an inspiring blend of academic and creative freedom along with access to world-class resources to empower you in pursuing your research ambitions.

Duties

• Assist in the development and optimization of AI models for healthcare applications particularly in natural language processing.
• Implement machine learning and deep learning algorithms using Python TensorFlow PyTorch or similar frameworks.
• Implement LLM-based systems for extracting structured data from clinical notes and unstructured medical text.
• Conduct data preprocessing feature engineering and exploratory data analysis on clinical and genomic datasets.
• Collaborate with researchers to analyze and interpret AI-generated insights for improving patient care.
• Assist in preparing research manuscripts presentations and technical reports.
• Participate in team meetings brainstorming sessions and contribute to research discussions.
• Support the documentation and version control of AI models using GitHub.
• Conduct literature reviews to stay up-to-date with emerging AI methodologies in computational biology and healthcare.

Qualifications :

• Must be 16 years of age or older per UHN policy.
• Must be enrolled in an undergraduate or postgraduate program in Computer Science Biomedical Engineering Computational Biology Data Science or a related field.
• Strong programming skills in Python and familiarity with AI/ML frameworks such as TensorFlow or PyTorch.
• Experience with fine-tuning open-source language models and developing in-house LLM solutions for data extraction tasks.
• Knowledge of natural language processing (NLP) applications in healthcare is an advantage.
• Familiarity with cloud computing platforms (e.g. AWS Google Cloud) and high-performance computing environments is a plus.
• Excellent problem-solving skills and ability to work independently and in a team environment.
• Strong analytical and communication skills with the ability to present research findings effectively.

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.

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 :

No

Employment Type :

Full-time