Research Assistant in Health Data Science and Machine Learning

About the Organization

The Research Institute of the McGill University Health Centre (RI-MUHC) is an internationally recognized biomedical and hospital research institute based in Montreal, Quebec. Affiliated with the Faculty of Medicine at McGill University and partially funded by the Fonds de recherche du Québec - Santé (FRQS), the institute focuses on advancing scientific discovery and innovation in patient-centered medicine.

Position Overview

Reporting to Dr. Esli Osmanlliu, the Research Assistant will support the PREDICT-ED project which aims to create and retrospectively assess machine-learning algorithms for forecasting pediatric Emergency Department patient volumes, wait times, and crowding. Utilizing aggregated institutional and publicly available data, the position is pivotal in developing predictive models with 6-hour and 24-hour horizons. The role blends quality improvement, patient safety, health data science, clinical informatics, and optimization of health systems.

Key Responsibilities

• Prepare, clean, integrate, and structure datasets from institutional and publicly accessible sources
• Develop predictive features related to pediatric Emergency Department metrics such as volume and crowding
• Work extensively with longitudinal and time-series data reflecting patient flow, operational resources, and contextual parameters
• Build, train, and benchmark machine-learning models specialized in time-series forecasting
• Conduct retrospective model evaluations employing relevant performance metrics
• Apply temporal validation techniques to minimize overfitting risks
• Maintain meticulous documentation of data pipelines, code, methodologies, assumptions, results, and limitations
• Collaborate with a diverse team comprising clinicians, researchers, informatics experts, and operational stakeholders
• Contribute to the preparation of reports, presentations, scientific abstracts, manuscripts, and materials for knowledge dissemination
• Support groundwork for forthcoming prospective evaluations of the models
• Engage with digital health initiatives alongside researchers, clinicians, and engineers
• Ensure system upkeep including troubleshooting and documentation for sustainability and knowledge transfer
• Assist with testing, quality assurance, and evaluation to ensure reliability and scalability of digital health systems

Performance Expectations

• Adhere strictly to scheduled project milestones encompassing data cleaning, model training, evaluation, and development of visualization tools for Emergency Department clinicians

Qualifications and Experience

• Master’s degree in Computer Science, Computer Engineering, Data Science, or a closely related discipline; doctoral degrees are considered an asset
• One to three years of relevant experience in scientific programming, data science, or machine learning
• Advanced proficiency in Python is essential
• Experience with machine-learning frameworks and libraries such as scikit-learn, PyTorch, TensorFlow, XGBoost, pandas, and NumPy
• Familiarity with longitudinal, time-series, health, or hospital operational data is advantageous
• Required language skills include fluency in French and advanced oral and written command of English for frequent interactions with international collaborators
• Strong programming capabilities, particularly in Python
• Clear and effective communication and technical documentation skills
• Experience with cloud platforms and application deployment
• Comprehensive understanding of supervised machine learning techniques
• Capability to produce organized, reproducible, and well-authored code
• Scientific rigor, independence, strong organizational skills, and attention to detail
• Excellent interpersonal communication skills
• Experience or awareness of MLOps practices including data/model pipeline management, version control, and experiment reproducibility
• Understanding of DevOps methodologies such as CI/CD, containerization, and cloud automation
• Familiarity with healthcare data privacy and security regulations (e.g., LPRPDE, HIPAA, GDPR)
• Proficiency in Microsoft Word, Excel, and Outlook

Additional Information

• Employment status: Temporary, full-time position (35 hours per week)
• Compensation: $30 per hour before taxes and deductions
• Work schedule: Monday to Friday, 9:00 AM to 5:00 PM
• Work location: 5252 de Maisonneuve Blvd., Montreal with hybrid work flexibility
• Contract duration: Fixed-term for 4 months beginning Summer 2026
• Application note: If submitting, cover letters should be included with the resume in a single document

Employee Benefits

• Four weeks of vacation annually, increasing to five weeks after five years of service
• Twelve paid personal/sick/family days
• Thirteen statutory holidays
• Modular group insurance including gender affirmation coverage
• Access to telemedicine services
• Participation in the RREGOP pension plan (defined benefit government plan)
• Professional development and training opportunities
• Child care services
• Corporate discounts (e.g., OPUS, Perkopolis)
• Affordable monthly parking rates
• Employee Assistance Program
• Recognition programs
• Flexible working options

Equity and Inclusion

The institute promotes equal opportunity employment, encouraging applications from racialized groups, women, Indigenous peoples, persons with disabilities, ethnic minorities, and 2SLGBTQIA+ individuals. Accommodations for applicants with disabilities are available upon request.

Important Note

This is a research position and not a hospital employment role.