APTPUO-summer 2026-MIA5100 Z

University of Ottawa

10d • Remote

About The Position

This course provides an in-depth exploration of the foundational topics in Machine Learning (ML) and Artificial Intelligence (AI), encompassing a broad range of concepts, algorithms, frameworks, methodologies, and practical applications. Topics will ranges from areas such as feature engineering, supervised and unsupervised learning, deep learning, natural language processing, and model deployment using state-of-art techniques. As part of this course, students are expected to develop the skills and knowledge necessary to design, implement, evaluate ML models, and deploy ML models effectively. Application areas will emphasize real-world contexts such as arts, business, social sciences, and law domains. The course format includes lectures, discussions, and lab sessions to facilitate comprehensive learning.

Requirements

• Ph.D. in AI, Machine Learning, DTI, Computer Science, Statistics, Mathematics, Engineering, or a related field.
• Demonstrated expertise in AI/Machine Learning, with a general focus on areas such as Machine Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP), and model deployment, including applications in real-world scenarios related to law, business, social sciences, and arts.
• Teaching experience at the graduate and/or undergraduate level, preferably in AI/Machine Learning or related fields.
• Hands-on experience with industry tools and technologies commonly used for developing and deploying Machine Learning, Deep Learning, and NLP algorithms, such as Python, TensorFlow, PyTorch, Scikit-Learn, Transformers, NLTK, SpaCy, Streamlit, Flask, etc.

Nice To Haves

• Preference will be given to candidates with experience in project-based learning or experiential learning approaches in AI/Machine Learning.

Benefits

• The University of Ottawa offers a generous pay and benefits package that includes a competitive salary, a defined benefit pension plan, group insurance coverage and an employee and family assistance program.

What This Job Offers

• Job Type: Part-time
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees