[Hiring] Part-Time Professor in Machine Learning @University of Ottawa

Role Description

Posting limited to: Professeur à temps-partiel régulier / Regular Part-Time Professor

• Location: Main Campus
• Academic Period: 2026 Fall Semester
• Course Title: FNDN & APP. MACHINE LEARNING
• Course Code: MIA5100
• Section: A
• Date Posted: 2026/06/05
• Applications must be received BEFORE: 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)
• Course type: B
• Posting type: Régulier / Regular
• Language of instruction: Anglais | English
• Competence in second language: Active
• Course Schedule: Mardi | Tuesday 19:00-22:00

Qualifications

• 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 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.

Requirements

• 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.
• Employees are required under provincial law to successfully complete all mandatory legislated training.
• The hiring process will be governed by the current APTPUO collective agreements.

Benefits

• 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.
• 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.
• Applicants with disabilities may contact [email protected] to communicate the accommodation need.
• All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.