Posting Reason:

New Position

Location:

Main Campus

Academic Period:

2027 Winter Semester

Faculty:

Faculté de génie / Faculty of Engineering

Academic Unit:

École de conception et d’innovation pédagogique en génie \\ School of Engineering Design and Teaching Innovation

Course Title:

Systems Integration

Course Code:

SYS5180

Section:

Course 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. If you are invited to continue the selection process, please notify us of any adaptive measures you might require. Information you send us will be handled respectfully and in complete confidence. Employees are required under provincial law to successfully complete all mandatory legislated training. The list of training may be modified by provincial law.

The hiring process will be governed by the current APTPUO collective agreements; you can click here for the main unit, here for the OLBI unit, or here for the Toronto/Windsor unit to find out more.

The University of Ottawa embraces diversity and inclusion in the workplace. We are passionate about our people and committed to employment equity. We foster a culture of respect, teamwork and inclusion, where collaboration, innovation, and creativity fuel our quest for research and teaching excellence. While all qualified persons are invited to apply, we welcome applications from qualified Indigenous persons, racialized persons, persons with disabilities, women and LGBTQIA2S+ persons. The University is committed to creating and maintaining an accessible, barrier-free work environment. The University is also committed to working with applicants with disabilities requesting accommodation during the recruitment, assessment and selection processes. Applicants with disabilities may contact vra.affairesprofessorales@uottawa.ca to communicate the accommodation need. All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.

Prior to May 1, 2022, the University required all students, faculty, staff, and visitors (including contractors) to be fully vaccinated against Covid-19 as defined in Policy 129 – Covid-19 Vaccination. This policy was suspended effective May 1, 2022 but may be reinstated at any point in the future depending on public health guidelines and the recommendations of experts.