Description
:Posting limited to:
Professeur à temps-partiel régulier / Regular Part-Time ProfessorDate Posted (YYYY/MM/DD):
2026/06/05Applications must be received BEFORE (YYYY/MM/DD):
2026/07/06Expected Enrolment:
30Approval date:
2026/06/05Number of credits:
3Work Hours:
39Hourly 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:
BPosting type:
Régulier / RegularLanguage of instruction:
Anglais | EnglishCompetence in second language:
ActiveCourse Schedule:
Mardi | Tuesday 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 onlineAn acceptable level of education and/or experience could be viewed as being equivalent to the educational required and/or demonstrated experience.
APTPUO Fall 2026- MIA5100- (ONLINE) • Ottawa, ON, CA
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