CUPE-Summer TA MIAZZ; online

Description

Unless specified below, specific allocation of hours to various tasks should be articulated in a description of work negotiated and signed by you and the supervising professor prior to the commencement of work.

Number of positions:

Expected Enrolment:

Work

Start Date:

Work End Date:

Total

Work Hours:

Hourly Rate:

The academic year starts on September 1 and ends on August 31.

Undergraduate students will be paid at the lower rate; while graduate students will be paid at the higher rate.

These rates do not included vacation pay nor statutory pay.

These rates will be applied until a new collective agreement is ratified. Retro will be paid after the ratification.

Language of Work:

Requirements and Nature of Work:

Must have strong theoretical knowledge of foundational AI/ML techniques such as statistical learning theory, supervised and unsupervised learning, deep learning, NLP, computer vision with applications to real-world use cases. Hands-on experience with industry tools and libraries commonly used for AI/ML model development (e.g., Python, Scikit-learn, Keras, NLTK, Spa Cy, etc.), as well as knowledge of application deployment, is required. Should have excellent communication skills and the ability to simplify complex topics to support student comprehension.

Preference will be given to candidates who have completed a related course with a minimum grade of A, or have prior experience as a teaching assistant for a similar course, and/or worked on AI/ML projects in an industry setting.

Additional Information and/or Comments:

All University of Ottawa employees are required under provincial law to successfully complete all mandatory legislated training offered by the University. The list of training requirements may be modified by provincial law.