Assistant Professor, Teaching Stream

Position Overview The Edward S. Rogers Sr. Department of Electrical and Computer Engineering (ECE) in the Faculty of Applied Science & Engineering at the University of Toronto invites applications for a full-time teaching stream position in the area of Artificial Intelligence and Deep Learning. The appointment will be at the rank of Assistant Professor, Teaching Stream, with an anticipated start date of July 1, 2026. Eligibility and Qualifications Applicants must have a PhD degree in Electrical and Computer Engineering, or a related field by the time of appointment, or shortly thereafter with a demonstrated record of excellence in teaching. Candidates must demonstrate teaching experience in a degree-granting program, including lecture preparation and delivery, curriculum development, and development of online material/lectures. Additionally, candidates must possess a demonstrated commitment to excellent pedagogical inquiry and a demonstrated interest in teaching-related scholarly activities at the graduate level. Teaching Expertise We seek candidates with teaching skills and expertise in the development and deployment of deep learning-based software and applications. Candidates should have knowledge of the fundamental theory of deep learning and significant experience in developing software applications that employ neural network and deep learning approaches to computer vision, natural language processing, and reinforcement learning. Experience in deploying industrial applications of deep learning is required. Graduate-level subjects to be taught include core deep learning/software, machine learning in production, introduction to reinforcement learning, and data science methods/quantitative analysis. Experience with biomedical applications of deep learning would be an asset. Candidates should also be able to teach courses in the existing curricula, create new courses, and demonstrate teaching effectiveness. Eligibility and willingness to register as a Professional Engineer in Ontario is highly desirable. Evidence of Teaching Excellence Evidence of excellence in teaching and a commitment to pedagogical inquiry can be demonstrated by previous teaching experience and accomplishments, the teaching dossier submitted as part of the application (with required materials outlined below), and strong letters of reference from referees of high standing familiar with relevant aspects of the applicant’s work. Equity, Diversity, and Inclusion Equity, diversity, and inclusion (EDI) are essential to academic excellence and the department’s success. Evidence of a commitment to EDI must be demonstrated by a statement submitted with the application, describing teaching that incorporates a focus on underrepresented communities, the development of inclusive pedagogies, views, experiences, and/or plans furthering EDI via student mentorship, pedagogy, outreach, and/or other activities. Salary Salary will be commensurate with qualifications and experience. Faculty and Location The Faculty of Applied Science and Engineering offers opportunities for collaborative and interdisciplinary research and teaching, and the excitement of working with a diverse student population. Established in 1873, the Faculty of Engineering has earned an international reputation for excellence. Toronto provides access to leading policy and decision makers, and is a vibrant, cosmopolitan, safe city. For more information about the Faculty of Applied Science and Engineering, visit https://engineering.utoronto.ca. Application Process All qualified candidates are invited to apply online by clicking the link below. Applicants must submit a cover letter outlining suitability to teach at the graduate level; a current curriculum vitae; a teaching dossier including a summary of previous teaching experience and accomplishments, a teaching statement, sample course syllabi and materials, and teaching evaluations; and an EDI statement. Applicants must provide the name and contact information of three references. The University of Toronto’s recruiting tool will automatically solicit and collect letters of reference from each referee within 48 hours after an application is submitted. Applicants are responsible for ensuring referees submit recent letters (dated, signed) by the closing date. At least one reference letter must primarily address teaching. Applications without three reference letters will not be considered. Submission guidelines can be found at https://uoft.me/how-to-apply. Your CV and cover letter should be uploaded into the dedicated fields. Please combine additional application materials into one or two files in PDF/MS Word format. Applications submitted in any other way will not be considered. If you have any questions, contact the ECE department at eceoffice@ece.utoronto.ca. All application materials, including recent reference letters, must be received by December 3, 2025. Priority for Canadians and Permanent Residents All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority. Diversity Statement The University of Toronto embraces diversity and builds a culture of belonging that increases capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. We value applicants who have demonstrated a commitment to EDI and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission. Diversity Survey As part of your application, you will be asked to complete a brief Diversity Survey. This survey is voluntary. Any information directly related to you is confidential and cannot be accessed by search committees or human resources staff. Results will be aggregated for institutional planning purposes. For more information, see http://uoft.me/UP. Accessibility Statement The University strives to be an equitable and inclusive community and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission. Our commitment to the Accessibility for Ontarians with Disabilities Act (AODA) means we strive to make recruitment, assessment, and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities. If you require any accommodations at any point during the application and hiring process, please contact uoft.careers@utoronto.ca. Apply Click here to apply: https://jobs.utoronto.ca/job/Toronto-Assistant-Professor%2C-Teaching-Stream-Artificial-Intelligence-and-Deep-Learning-ON/596957917/ #J-18808-Ljbffr