Required Qualifications:
• As per the Collective Agreement, must be enrolled as a student in the Fall 2025 semester.
• Must have excellent organizational, time management and communications skills. Must be available to attend and conduct scheduled office hours throughout the entire semester, attend weekly meetings, if applicable, as assigned by the instructor.
• Must have excellent writing skills (as evidenced by peer reviewed publications) and be able to effectively critique student assignments in writing.
• Must have excellent verbal communications skills (as evidenced by a history of presentations at various venues).
• Must have strong familiarity with the principles of Academic Integrity.
• Must provide evidence of competence in data management in a Unix environment, including: (a) the ability to load and manipulate structured text data, including delimited files, using the Python programming language, (b) the ability to manage files and directories on Unix system, (c) control processes and (d) transfer files.
• Must be a current graduate student (MSc or PhD) in Computer Science.
• Must have completed graduate-level coursework or research in Artificial Intelligence or Machine Learning.
• Must demonstrate a working knowledge of course topics such as intelligent agents, search algorithms, constraint satisfaction, knowledge representation, probabilistic reasoning, deep learning, and reinforcement learning.
• Must be proficient in Python, and able to support students working with AI/ML libraries such as Scikit-learn, TensorFlow, or PyTorch.
Preferred Qualifications:
• Experience as a teaching assistant or grader for a senior undergraduate or graduate AI or ML course.
• Familiarity with the textbook Artificial Intelligence: A Modern Approach (4th Edition) and related teaching materials.
• Experience with Jupyter Notebooks, GitHub, and collaborative code review workflows.
• Experience supporting or evaluating student research projects involving applied AI/ML, or time-series data.
• Exposure to tools and concepts used in explainable AI (e.g., SHAP, attention visualization).
• A publication or thesis related to Artificial Intelligence or Machine Learning.