Description
:•Develop and deliver engaging lectures on mathematical concepts for AI
• Create comprehensive course materials that bridge theoretical concepts with practical AI applications
• Design assignments and projects that reinforce mathematical foundations in AI contexts
• Conduct fair and thorough assessments, including exams and quizzes
• Provide timely and constructive feedback to students
• Hold regular office hours to support student learning and address questions
• Collaborate with faculty to ensure curriculum alignment with other AI and machine learning courses
• Incorporate innovative teaching methodologies that enhance student engagement in mathematical concepts
• Utilize brightspace for course administration
Posting limited to:
Professeur à temps-partiel régulier / Regular Part-Time Professor
Date Posted (YYYY/MM/DD):
2026/05/20
Applications must be received BEFORE (YYYY/MM/DD):
2026/06/21
Expected Enrolment:
40
Approval date:
2026/05/20
Number of credits:
3
Work Hours:
39
Hourly Rate:
Enseignement / Teaching: $239.47 (2024-2025)
The academic year starts on September 1 and ends on August 31.
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.
Course type:
B
Posting type:
Régulier / Regular
Language of instruction:
Anglais | English
Competence in second language:
Active
Course Schedule:
Mardi | Tuesday 8:30-11:30 - -
Requirements:
Required:
- Ph.D. in Mathematics, Computer Science, Electrical Engineering, or a closely related field with a strong focus on AI and machine learning
- Demonstrated expertise in the mathematical foundations of AI and machine learning
- Minimum of 3 years teaching experience at the graduate level
- Excellent communication skills, with the ability to explain complex mathematical concepts clearly
- Proficiency in using mathematical and AI software packages (e.g., MATLAB, Python with NumPy/SciPy)
- Commitment to fostering an inclusive and diverse learning environment
Preferred:
- Industry experience applying mathematical concepts in AI and machine learning contexts
- Familiarity with interdisciplinary applications of AI in engineering and other fields
Additional Information and/or Comments:
An acceptable level of education and/or experience could be viewed as being equivalent to the educational required and/or demonstrated experience.