APTPUO Fall 2026- MIA5150-REPOST (ONLINE) Topic (Generative AI and (LLMs)

Posting Reason:

New Position

Location:

Main Campus

Academic Period:

2026 Fall Semester

Faculty:

Faculté de génie / Faculty of Engineering

Academic Unit:

École de conception et dinnovation pédagogique en génie School of Engineering Design and Teaching Innovation

Course Title:

Generative AI and Large Language Models

Course Code:

MIA5150

Section:

B

Course Description:

Foundations and practices of Generative AI and Large Language Models (LLMs) covering the full lifecycle from model development to deployment. Explore generative model families including Transformers autoregressive models diffusion models GANs and VAEs and their multimodal applications across text image audio and video. Modern techniques such as fine-tuning parameter-efficient training in-context learning contrastive learning retrieval-augmented generation (RAG) and multi-agent systems for enabling complex reasoning coordination and autonomous task execution are discussed. Key practices in prompt engineering inference optimization safety and alignment and responsible AI deployment. Practical applications across diverse domains.
Prerequisite: MIA5100 MIA5126 or equivalent.

Posting limited to:

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

Date Posted (YYYY/MM/DD):

2026/05/26

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

2026/08/23

Expected Enrolment:

30

Approval date:

2026/07/22

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 19:00-22:00 - -

Requirements:

• Ph.D. in Computer Science Data Science Artificial Intelligence Machine Learning Software Engineering DTI Engineering or a closely related field.
• Demonstrated expertise in Generative AI and Large Language Models (LLMs) including areas such as Transformers diffusion models GANs VAEs retrieval-augmented generation (RAG) prompt engineering fine-tuning and multimodal AI systems.
• Experience developing or applying modern AI/ML workflows using industry-standard tools and frameworks such as Python PyTorch TensorFlow Hugging Face Transformers LangChain vector databases and cloud-based AI platforms.
• Knowledge of AI deployment practices including inference optimization parameter-efficient training model evaluation safety alignment responsible AI and scalable deployment architectures.
• Knowledge of emerging agentic AI systems and multi-agent orchestration frameworks for autonomous reasoning planning and task execution.
• Teaching experience at the graduate/undergraduate level in Artificial Intelligence Machine Learning Data Science or related disciplines
• Demonstrated ability to translate complex AI concepts into applied industry-relevant learning experiences through lectures labs projects and case studies.
• Relevant industry experience in AI/ML development applied Generative AI MLOps or AI product development is considered an asset.

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 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.