PT Prof; APTPUO; DTI- Winter

Position: PT Prof (APTPUO) - DTI6402 A - Winter 2027
Posting Reason:
New Position

Location:

Main Campus
Academic Period: 2027 Winter Semester
Faculty:
Faculté de génie / Faculty of Engineering
Academic Unit: École de conception et d’innovation pédagogique en génie   School of Engineering Design and Teaching Innovation
Course

Title:

Affective and Persuasive Computing
Course Code: DTI
6304
Section: A
Course

Description:

Posting limited to:
Professeur à temps-partiel régulier / Regular Part-Time Professor
Date Posted (YYYY/MM/DD): 2026/11/02
Applications must be received BEFORE (YYYY/MM/DD): 2026/12/03
Expected Enrolment: 50
Approval date: 2026/11/02
Number of credits: 3

Work Hours:

39
Hourly Rate: Enseignement / Teaching: $239.47 )
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: C
Posting type: Régulier / Regular
Language of instruction:
Anglais | English
Competence in second language:
Active
Course

Schedule:

Vendredi | Friday 17:30-20:30 -
- Requirements:
The candidate should have a PhD or be currently completing a PhD in Digital Transformation and Innovation, Electrical and Computer Engineering, Computer Science, or a closely related field, with a strong background in affective computing, artificial intelligence, machine learning, and human‑computer interaction. The candidate should have demonstrated knowledge and experience in developing emotion recognition and affect estimation algorithms using deep learning techniques, including the processing and analysis of physiological signals, facial expressions, speech, text, and multimodal data.

Experience with multimodal fusion, neural network architectures, and AI-based intelligent interactive systems is highly desirable. The candidate should also have knowledge of persuasive technology, persuasion design strategies, and their applications in serious games, virtual reality, and digital health. Familiarity with modern AI technologies, including large language models and multimodal AI systems, as well as proficiency in Python and machine learning frameworks such as Tensor Flow or PyTorch, would be considered an asset.

Previous university‑level teaching experience and research contributions in affective computing, artificial intelligence, or related areas are highly desirable.
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 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.affa to communicate the accommodation…