Part Time Professor 2026 Winter CEG4195/SEG4180
SITE, Canada
University of Ottawa
Location:
Main CampusSession:
2026 Winter Semester | Trimestre d'hiverFaculty:
Faculté de génie / Faculty of EngineeringUnit:
EECS_PTCourse Title:
Applied Machine Learning for Computer EngineeringCourse Code:
CEG4195Section:
Course Description:
Basic theory of machine learning. Application to engineering problems. Supervised and unsupervised learning. Neural networks. Convolutional neural nets. Large language models. Tools for developing machine learning models and software applications that incorporate machine learning. Quality assurance and operations (MLOps) of machine learning systems. Feature engineering and prompt engineering. Case studies in various domains.Posting limited to:
Professeur à temps-partiel régulier / Regular Part-Time ProfessorDate Posted:
June 04, 2025Applications must be received BEFORE:
July 05, 2025Expected Enrolment:
N/AApproval date:
June 04, 2025Number of credits:
3Work Hours:
39Course type:
BPosting type:
Régulier / RegularLanguage of instruction:
Anglais | EnglishCompetence in second language:
PassiveCourse Schedule:
Lundi | Monday 14:30-16:00 Jeudi | Thursday 16:00-17:30 -Requirements:
Excellent knowledge of course subject matter, demonstrated by having taught similar or related courses, or demonstrated by relevant work experience. Applicants must also be licensed as a Professional Engineer. Regular applicants must have a doctorate and it should be in a field related to the course (especially in the case where the course is more specialized), if not, they must have a relevant work experience in a field related to the course, after having obtained their Ph.D.
Please include your P.Eng. License number and province of registration when applying.
Additional Information and/or Comments:
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Engineering Feature engineering LLMs Machine Learning ML models MLOps Prompt engineering Research Teaching Unsupervised Learning
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