APTPUO Winter 2027- MIA5100- (ONLINE)

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:

FNDN & APP. MACHINE LEARNING

Course Code:

MIA5100

Section:

A

Course Description:

Posting limited to:

Professeur à temps-partiel régulier / Regular Part-Time Professor

Date Posted (YYYY/MM/DD):

2026/06/05

Applications must be received BEFORE (YYYY/MM/DD):

2026/07/06

Expected Enrolment:

30

Approval date:

2026/06/05

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:

Jeudi | Thursday 19:00-22:00 - -

Requirements:

Ph.D. in AI, Machine Learning, DTI, Computer Science, Statistics, Mathematics, Engineering, or a closely related field with a strong focus on AI/ML.

• Demonstrated industry experience in AI/ML, including demonstrated involvement in designing, building, and deploying machine learning systems in real-world applications.
• Applied expertise in AI/ML, including areas such as Machine Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP), and model deployment, with evidence of real-world application in domains such as law, business, social sciences, or the arts.
• Hands-on experience with industry-standard AI/ML tools and frameworks, including Python and libraries such as Scikit-learn, PyTorch or TensorFlow, NLP frameworks, Transformer-based models, and familiarity with ML pipelines and deployment workflows (e.g., Streamlit or similar tools).
• Experience with cloud-based ML systems, including AWS, Azure, or Google Cloud, with demonstrated ability to deploy models in applied environments.
• Experience delivering end-to-end AI/ML workflows, including data preparation, model development, evaluation, and deployment, in applied or industry settings.
• Teaching experience in AI/ML at the graduate and/or undergraduate level.
• Proven AI/ML experience in industry, as well as experience incorporating project-based or experiential learning approaches in AI/ML.

Additional Information and/or Comments:

The course is online

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.