About the Project

This research project aims to develop a machine learning (ML) model to predict short-term congestion in air cargo operations. The research integrates operational logistics, applied AI, and stakeholder engagement with aviation industry partners (Westjet Cargo). The RA will support the PI in reviewing literature, building and cleaning datasets, running baseline ML models, and preparing visualizations and summary materials. The project is supervised by Dr. Mina Enayatollahi, Assistant Professor of Aviation, Bissett School of Business, and contributes to ongoing collaboration between MRU and WestJet.

About the Role

The RA will work under direct supervision and gradually take on increasing responsibilities. The position will work approximately 6-10 hours per week for 9 months with the possibility of extension.

Responsibilities

• Conduct literature reviews on air cargo operations, congestion modeling, and ML in logistics
• Assist in compiling and formatting operational or simulated datasets
• Support the development and testing of predictive ML models using Python
• Help evaluate model performance using standard metrics
• Prepare visualizations and summaries for reports, presentations, or posters
• Participate in weekly check-ins and contribute to knowledge mobilization activities

Qualifications

• Interest in aviation operations, air logistics, or applied data science
• Familiarity with Python and data tools (e.g., pandas, matplotlib, Jupyter notebooks)
• Strong attention to detail, critical thinking, and willingness to learn
• Able to work independently while taking direction on project tasks
• Reliable and communicative; able to meet on campus weekly

Preferred (but not required)

• Coursework in aviation management, operations research, or statistics
• Prior experience with machine learning or data-driven projects
• Familiarity with Google Colab, GitHub, or cloud-based tools

Salary:                   $21.23 - $26.81 per hour

Closing Date:        December 26, 2025