AI in Biomedicine – Research Intern

Job Description

Union: Non-Union
Number of vacancies:  1
Site: Toronto General Hospital
Department:  Research
Reports to:  Senior Scientist I
Hours: 37.5 hours per week
Shifts: Days
Status: Temporary Full-Time
Closing Date: November 30, 2025

Position Summary:

The Peter Munk Cardiac is thrilled to announce an exceptional opportunity for a research student to join our dynamic team. You will be working directly under the visionary leadership of our Chief AI Scientist. We are looking for candidates enrolled in an undergraduate program and an impressive publication record, specializing in areas such as Computational Biology, Natural Language Processing (NLP), Computer Vision, or Human-Computer Interaction. 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 computational biology. 
• Implement machine learning and deep learning algorithms using Python, TensorFlow, PyTorch, or similar frameworks. 
• 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 biological datasets, genomic data analysis, or computational modeling is an asset. 
• Knowledge of natural language processing (NLP) and computer vision 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.