Academic Assistant - CIND830 (D20) Python Programming Data Science | Mon | Sep 14-Dec 21 | 6:30-9:30

Toronto Metropolitan University is Canada's leader in innovative, career-focused education and a university clearly on the move. It is a distinctly urban university with a focus on innovation and entrepreneurship. Toronto Metropolitan University has a mission to serve societal need and a long-standing commitment to engaging its community.

Guided by a bold Academic Plan, an ambitious research agenda, and a Master Plan to revitalize the campus and surrounding neighbourhood, Toronto Metropolitan University is the most applied-to university in Ontario relative to available spaces, and its reputation with business and community leaders continues to rise.

We offers more than 100 undergraduate and graduate programs. Culturally diverse and inclusive, the university is home to 38,950 students, including 2,300 master's and PhD students, nearly 2,700 faculty and staff, and more than 170,000 alumni worldwide. Research at Toronto Metropolitan University is on a trajectory of success and growth: externally funded research has doubled in the past four years. The G. Raymond Chang School of Continuing Education is Canada's leading provider of university-based adult education. The university's focus on innovation and entrepreneurship is represented most distinctly by the Digital Media Zone, a place for students to collaborate and bring their digital ideas to the marketplace.

Toronto Metropolitan University is reshaping the downtown core of Toronto with three new buildings: the Mattamy Athletic Centre at the Gardens, the Toronto Metropolitan University Image Centre in the heart of campus, and a Student Learning Centre on Yonge Street. In addition, currently in progress is the development of a new multipurpose building, the Church Street development (CSD). This new building will be located just north of Dundas on Church Street and will be home to four academic health services programs, Toronto Met. University food services, administration, and a student residence.

Qualifications

GA applicants are evaluated based on the qualifications and criteria stated below:

• Enrolled in a Master’s or Ph.D. program (preference to Doctoral, then Master’s).
• Minimum overall standing: B+ (or equivalent).
• Proficiency with Python, including object-oriented programming (classes, objects, inheritance/polymorphism), algorithm analysis (Big-O), and core data structures (lists, tuples, dictionaries, arrays, stacks, queues, trees).
• Experience designing and implementing non-trivial Python programs (e.g., multi-module projects or small applications).
• Evidence of applied Python projects focused on OOP, data structures, and algorithms in Jupyter notebooks with clear tests and documentation.
• Background in Computer Science or a closely related field.
• Hands-on experience with Microsoft Azure virtual machines or labs.
• Previous performance evaluation as a Teaching/Graduate Assistant at a University, if applicable.

Applicants not registered as TMU students will be considered if no qualified TMU student is available.

Attendance: GA must attend all lab sessions held by the designated instructor and be fully prepared. 

September 1, 2024 to August 31, 2025

Master -  $49.93 per hour
PhD -      $53.91 per hour

September 1, 2025 to August 31, 2026

Master -  $51.17 per hour
PhD -  $55.26 per hour

Coordination - 2 Hours: Plan, prepare, and meet with the instructor (lab prep, grading rubrics, alignment with course outcomes). 

Lab Support - 18 Hours:  Attend 12 lab sessions and actively demonstrate tools, participate in student discussions, and support technical procedures, lab tutorials, and live-session activities.

Grading - 18 Hours:  Grade assignments in terms of the course rubric; assess process and findings; provide feedback on all rubric criteria and return marks within the timeframe specified by course policy.

Discussion Board - 5 Hours: Monitor and participate in the online course shell; address student concerns and questions thoroughly, and provide complete, timely replies in line with course policy.

Review Sessions - 2 Hours: Conduct one 2-hour or two 1-hour review sessions (for mid-term and/or final).

Enter # of Students