Active Openings
Faculty opportunities
Date Posted: 05/04/2023
Closing Date: 06/15/2023, 11:59PM ET
Req ID: 30843
Job Category: Faculty - Teaching Stream, Contractually Limited Term Appointment
Faculty/Division: Faculty of Applied Science & Engineering
Department: Edward S. Rogers Sr. Department of Electrical and Computer Engineering
Campus: St. George (Downtown Toronto)
Description:
The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE) in the Faculty of Applied Science and Engineering (FASE) at the University of Toronto invites applications for a three-year Contractually Limited Term Appointment (CLTA) in the field of software engineering. The appointment will be at the rank of Assistant Professor, Teaching Stream, with an anticipated start date of September 1 2023, with the possibility of a two-year extension.
Applicants must have earned a PhD degree in electrical and computer engineering or a related area by the time of appointment, or shortly thereafter with a demonstrated record of excellence in teaching. We seek candidates whose teaching interests complement and enhance our existing departmental strengths, and address the needs of a growing professional masters degree program. Candidates must have 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.
We seek candidates with teaching skills, expertise and experience in industrial-level and academic software engineering practices and web front-end and back-end application development. This includes extensive knowledge of industrial practice and theory of software engineering, web development – client-side UI and server-side database and cloud-based server and serverless management and deployment of software. Knowledge of human-computer interaction with AI would be an asset. Candidates are expected to be able to teach courses in existing curricula and to create some new courses, and to demonstrate their ability to teach.
Evidence of excellence in teaching and a commitment to excellent pedagogical inquiry can be demonstrated through teaching accomplishments, awards and accolades, presentations at significant conferences, the teaching dossier submitted as part of the application (with required materials outlined below) as well as strong letters of reference from referees of high standing familiar with relevant aspects of the applicant’s work.
Equity, diversity, and inclusion (EDI) are essential to academic excellence and to the success of our department. Evidence of a commitment to EDI will be demonstrated by a statement describing views, experiences and/or plans furthering EDI via student mentorship, pedagogy, outreach, and/or other activities.
Salary is commensurate with qualifications and experience.
All qualified candidates are invited to apply online by clicking the link below. Applicants must submit a cover letter outlining the suitability to teach at the graduate level; a current detailed curriculum vitae; and a complete teaching dossier including a strong teaching statement, sample syllabi and course 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 once an application is submitted (this happens overnight). Applicants remain responsible for ensuring that references submit letters (on letterhead, dated and signed) by the closing date. At least one reference letter must primarily address the candidate’s teaching. More details on the automatic reference letter collection, including timelines, are available in the FAQ’s.
Submission guidelines can be found at http://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. If you have any questions about this position, please contact Inna Latypova at eceoffice@utoronto.ca.
All application materials, including reference letters, must be received by June 15, 2023.
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 is building a culture of belonging that increases our 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 equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.
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, please 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.
The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our 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.
Date Posted: 05/04/2023
Closing Date: 06/15/2023, 11:59PM ET
Req ID: 30842
Job Category: Faculty - Teaching Stream, Contractually Limited Term Appointment
Faculty/Division: Faculty of Applied Science & Engineering
Department: Edward S. Rogers Sr. Department of Electrical and Computer Engineering
Campus: St. George (Downtown Toronto)
Description:
The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE) in the Faculty of Applied Science and Engineering (FASE) at the University of Toronto invites applications for a three-year Contractually Limited Term Appointment (CLTA) in the field of artificial intelligence and deep learning. The appointment will be at the rank of Assistant Professor, Teaching Stream, with an anticipated start date of September 1, 2023, with the possibility of a two-year extension.
Applicants must have earned a PhD degree in electrical and computer engineering or a related area by the time of appointment, or shortly thereafter with a demonstrated record of excellence in teaching. We seek candidates whose teaching interests complement and enhance our existing departmental strengths, and address the needs of a growing professional masters degree program. Candidates must have 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.
We seek candidates with teaching skills and expertise in the development and deployment of deep learning-based software and applications. This includes knowledge of the fundamental theory of deep learning along with significant experience in the development of software applications that employ neural network and deep learning approaches to computer vision, natural language processing, and the use of reinforcement learning. The candidate should have experience in the deployment of industrial applications of deep learning. Graduate-level subjects to be taught include core deep learning/software, machine learning “OPs” in production, introduction to reinforcement learning and data science methods/quantitative analysis. Experience with biomedical applications of deep learning would be an asset. Candidates are expected to be able to teach courses in existing curricula and to create some new courses, and to demonstrate their ability to teach.
Evidence of excellence in teaching and a commitment to excellent pedagogical inquiry can be demonstrated through teaching accomplishments, awards and accolades, presentations at significant conferences, the teaching dossier submitted as part of the application (with required materials outlined below) as well as strong letters of reference from referees of high standing familiar with relevant aspects of the applicant’s work.
Equity, diversity, and inclusion (EDI) are essential to academic excellence and to the success of our department. Evidence of a commitment to EDI will be demonstrated by a statement describing views, experiences and/or plans furthering EDI via student mentorship, pedagogy, outreach, and/or other activities.
Salary is commensurate with qualifications and experience.
All qualified candidates are invited to apply online by clicking the link below. Applicants must submit a cover letter outlining the suitability to teach at the graduate level; a current detailed curriculum vitae; and a complete teaching dossier including a strong teaching statement, sample syllabi and course 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 once an application is submitted (this happens overnight). Applicants remain responsible for ensuring that references submit letters (on letterhead, dated and signed) by the closing date. At least one reference letter must primarily address the candidate’s teaching. More details on the automatic reference letter collection, including timelines, are available in the FAQ’s.
Submission guidelines can be found at http://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. If you have any questions about this position, please contact Inna Latypova at eceoffice@utoronto.ca.
All application materials, including reference letters, must be received by June 15, 2023.
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 is building a culture of belonging that increases our 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 equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.
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, please 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.
The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our 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.
Postdoctoral Fellow
Areas of Research: Monolithic Quantum Processors in Production CMOS
Description of duties:
- Operate and maintain a 2K Lake Shore Cryotronics CPX-VF-LT probestation with adjustablevertical field magnet.
- Design and characterize 1D linear quantum dot (QD), double QD with selective back gate, andlinear qubit arrays with more than 512 qubits.
- Design along with Prof. Voinigescu, characterize, and demonstrate a scalable monolithic quantumprocessor consisting of a linear array of 1024 single- and double hole-spin qubits capacitivelycoupled to a linear array of readout QDs and of the associated individual-per-qubit control andreadout electronics.
Salary: $80,000-85,000
Required qualifications:
- A PhD in Experimental Physics, Engineering Physics or Electrical and Computer Engineeringwith a focus on Quantum Computing Hardware.
- Strong theoretical background in semiconductor spin qubits, spin control and readout principles,circuits and qubit measurement protocols (Larmor and Rabi frequencies, T1, T2, single and two-spin gates, randomized benchmarking) at cryogenic temperatures below 4 K.
- Familiarity with microwave and mm-wave lab equipment: Vector Network Analyzer, NoiseFigure Analyzer, Real Time Oscilloscope, Arbitrary Waveform Generator, Lock-in-Amplifier,Semiconductor Parameter Analyzer, and Spectrum Analyzer testing from dc to 300 GHz and on-wafer probing of devices and circuits at cryogenic temperatures.
- Experience using state-of-the-art IC and semiconductor device CAD tools:
- Cadence Analog Artist Spectre RF, Composer, Virtuoso
- Sentaurus, QuantumATK or similar device simulators
- inductor, transformer and multiport EM design and modelling using EMX or equivalent 2.5Dor 3D electromagnetic simulator.
- Good understanding of and experience using 22nm FDSOI, 3nm/5nm FinFET CMOS, and SiGeBiCMOS technology process flow, device modelling and layout.
Application instructions: All individuals interested in this position must submit their CV and the names of two references, include a one-page description outlining your specific qualifications for this position to Professor Sorin Voinigescu.
Closing date: July 1, 2023
Supervisor: Professor Sorin Voinigescu
Expected start date: September 1, 2023 (or shortly thereafter)
Term: 2 years extendable to 3 years.
FTE: The normal hours of work are 40 hours per week for a full-time postdoctoral fellow (pro-rated for those holding a partial appointment) recognizing that the needs of the employee’s research and training and the needs of the supervisor’s research program may require flexibility in the performance of the employee’s duties and hours of work.
Employment as a Postdoctoral Fellow at the University of Toronto is covered by the terms of the CUPE 3902 Unit 5 Collective Agreement.
This job is posted in accordance with the CUPE 3902 Unit 5 Collective Agreement.
The University of Toronto is strongly committed to diversity within its community and especially welcomes applications from racialized persons / persons of colour, women, Indigenous / Aboriginal People of North America, persons with disabilities, LGBTQ2S+ persons, and others who may contribute to the further diversification of ideas.
See the PDF version of Job Posting - Postdoctoral Fellow.
Research opportunities
The Edward S. Rogers Sr. Department of Electrical & Computer Engineering fills Postdoctoral Fellow and Research Associate positions throughout the year.
Research associate positions are generally posted on the University of Toronto Careers website.
For possible Postdoctoral opportunities, please contact professors directly.
Administrative and technical staff
Administrative and technical staff positions are generally posted on the University of Toronto Careers website.
Teaching Assistantships (TAs) (CUPE 3902 Unit 1)
Teaching Assistant (CUPE3902 Unit 1) positions for Electrical & Computer Engineering courses only.
Eligibility
You must be a current or admitted U of T student or a postdoctoral fellow to be eligible.
Job postings
You can find TA job postings on the University of Toronto CUPE 3902 Unit 1 Job Posting Board.
- Fall-term courses: applications open in June, first round offers by mid-August
- Winter-term courses: applications open in October, first round offers by late November
Note: Emergency TA postings are posted throughout the year.
Application instructions
- Apply through the online TA Database (TAD) using your UTORid
- If you are an admitted graduate student you can use your JOINid
- Ensure you complete the Course Preferences section and upload a current Teaching resume in PDF format
- See Undergraduate Course Descriptions and Graduate Course Descriptions for course preferences
Note: TAs must complete the Teaching Assistant Training Program , FASE, AODA and Basic Occupational Health & Safety Training. See details on the Information for Current TAs page.
Course Instructors (CUPE 3902 Unit 1)
Eligibility
You must be a current or admitted U of T student or a postdoctoral fellow to be eligible.
Job postings
You can find CI job postings on the University of Toronto CUPE 3902 Unit 1 Job Posting Board.
Application instructions
Follow the instructions found on the job posting site.
Sessional Lecturers (CUPE 3902 Unit 3)
Sessional Lecturer (CUPE3902 Unit 3) positions for Electrical & Computer Engineering only.
Eligibility
The eligibility criteria are determined on a position-by-position basis. Check the posting of the position you are applying for.
Job postings
You can find Sessional Lecturer positions on the University of Toronto Careers page under CUPE 3902 (Unit 3) Opportunities.
Note: Positions may become available unexpectedly throughout the year.
Application instructions
- Complete Unit 3 Application Form (rtf)
- Complete up-to-date Teaching Resume
- Submit both to ugta.ece@utoronto.ca
If you require an accommodation during the application or selection process, please contact: ugta.ece@utoronto.ca.
Note: Applications will be retained for 24 months. If you have submitted an application and resume, you will receive emails for specific job postings during this 24-month period.
General information
This notice is posted pursuant to the CUPE Local 3902 Unit 3 Collective Agreement. Please note that in accordance with that agreement, preference in hiring is given to qualified persons advanced to the rank of Sessional Lecturer II or Sessional Lecturer III in accordance with Article 14:12.
Benefits
Date Posted: 05/04/2023
Closing Date: 06/15/2023, 11:59PM ET
Req ID: 30842
Job Category: Faculty - Teaching Stream, Contractually Limited Term Appointment
Faculty/Division: Faculty of Applied Science & Engineering
Department: Edward S. Rogers Sr. Department of Electrical and Computer Engineering
Campus: St. George (Downtown Toronto)
Description:
The Edward S. Rogers Sr. Department of Electrical & Computer Engineering (ECE) in the Faculty of Applied Science and Engineering (FASE) at the University of Toronto invites applications for a three-year Contractually Limited Term Appointment (CLTA) in the field of artificial intelligence and deep learning. The appointment will be at the rank of Assistant Professor, Teaching Stream, with an anticipated start date of September 1, 2023, with the possibility of a two-year extension.
Applicants must have earned a PhD degree in electrical and computer engineering or a related area by the time of appointment, or shortly thereafter with a demonstrated record of excellence in teaching. We seek candidates whose teaching interests complement and enhance our existing departmental strengths, and address the needs of a growing professional masters degree program. Candidates must have 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.
We seek candidates with teaching skills and expertise in the development and deployment of deep learning-based software and applications. This includes knowledge of the fundamental theory of deep learning along with significant experience in the development of software applications that employ neural network and deep learning approaches to computer vision, natural language processing, and the use of reinforcement learning. The candidate should have experience in the deployment of industrial applications of deep learning. Graduate-level subjects to be taught include core deep learning/software, machine learning “OPs” in production, introduction to reinforcement learning and data science methods/quantitative analysis. Experience with biomedical applications of deep learning would be an asset. Candidates are expected to be able to teach courses in existing curricula and to create some new courses, and to demonstrate their ability to teach.
Evidence of excellence in teaching and a commitment to excellent pedagogical inquiry can be demonstrated through teaching accomplishments, awards and accolades, presentations at significant conferences, the teaching dossier submitted as part of the application (with required materials outlined below) as well as strong letters of reference from referees of high standing familiar with relevant aspects of the applicant’s work.
Equity, diversity, and inclusion (EDI) are essential to academic excellence and to the success of our department. Evidence of a commitment to EDI will be demonstrated by a statement describing views, experiences and/or plans furthering EDI via student mentorship, pedagogy, outreach, and/or other activities.
Salary is commensurate with qualifications and experience.
All qualified candidates are invited to apply online by clicking the link below. Applicants must submit a cover letter outlining the suitability to teach at the graduate level; a current detailed curriculum vitae; and a complete teaching dossier including a strong teaching statement, sample syllabi and course 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 once an application is submitted (this happens overnight). Applicants remain responsible for ensuring that references submit letters (on letterhead, dated and signed) by the closing date. At least one reference letter must primarily address the candidate’s teaching. More details on the automatic reference letter collection, including timelines, are available in the FAQ’s.
Submission guidelines can be found at http://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. If you have any questions about this position, please contact Inna Latypova at eceoffice@utoronto.ca.
All application materials, including reference letters, must be received by June 15, 2023.
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 is building a culture of belonging that increases our 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 equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.
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, please 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.
The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our 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.
Postdoctoral Fellow
Areas of Research: Monolithic Quantum Processors in Production CMOS
Description of duties:
- Operate and maintain a 2K Lake Shore Cryotronics CPX-VF-LT probestation with adjustablevertical field magnet.
- Design and characterize 1D linear quantum dot (QD), double QD with selective back gate, andlinear qubit arrays with more than 512 qubits.
- Design along with Prof. Voinigescu, characterize, and demonstrate a scalable monolithic quantumprocessor consisting of a linear array of 1024 single- and double hole-spin qubits capacitivelycoupled to a linear array of readout QDs and of the associated individual-per-qubit control andreadout electronics.
Salary: $80,000-85,000
Required qualifications:
- A PhD in Experimental Physics, Engineering Physics or Electrical and Computer Engineeringwith a focus on Quantum Computing Hardware.
- Strong theoretical background in semiconductor spin qubits, spin control and readout principles,circuits and qubit measurement protocols (Larmor and Rabi frequencies, T1, T2, single and two-spin gates, randomized benchmarking) at cryogenic temperatures below 4 K.
- Familiarity with microwave and mm-wave lab equipment: Vector Network Analyzer, NoiseFigure Analyzer, Real Time Oscilloscope, Arbitrary Waveform Generator, Lock-in-Amplifier,Semiconductor Parameter Analyzer, and Spectrum Analyzer testing from dc to 300 GHz and on-wafer probing of devices and circuits at cryogenic temperatures.
- Experience using state-of-the-art IC and semiconductor device CAD tools:
- Cadence Analog Artist Spectre RF, Composer, Virtuoso
- Sentaurus, QuantumATK or similar device simulators
- inductor, transformer and multiport EM design and modelling using EMX or equivalent 2.5Dor 3D electromagnetic simulator.
- Good understanding of and experience using 22nm FDSOI, 3nm/5nm FinFET CMOS, and SiGeBiCMOS technology process flow, device modelling and layout.
Application instructions: All individuals interested in this position must submit their CV and the names of two references, include a one-page description outlining your specific qualifications for this position to Professor Sorin Voinigescu.
Closing date: July 1, 2023
Supervisor: Professor Sorin Voinigescu
Expected start date: September 1, 2023 (or shortly thereafter)
Term: 2 years extendable to 3 years.
FTE: The normal hours of work are 40 hours per week for a full-time postdoctoral fellow (pro-rated for those holding a partial appointment) recognizing that the needs of the employee’s research and training and the needs of the supervisor’s research program may require flexibility in the performance of the employee’s duties and hours of work.
Employment as a Postdoctoral Fellow at the University of Toronto is covered by the terms of the CUPE 3902 Unit 5 Collective Agreement.
This job is posted in accordance with the CUPE 3902 Unit 5 Collective Agreement.
The University of Toronto is strongly committed to diversity within its community and especially welcomes applications from racialized persons / persons of colour, women, Indigenous / Aboriginal People of North America, persons with disabilities, LGBTQ2S+ persons, and others who may contribute to the further diversification of ideas.
See the PDF version of Job Posting - Postdoctoral Fellow.
Research opportunities
The Edward S. Rogers Sr. Department of Electrical & Computer Engineering fills Postdoctoral Fellow and Research Associate positions throughout the year.
Research associate positions are generally posted on the University of Toronto Careers website.
For possible Postdoctoral opportunities, please contact professors directly.
Administrative and technical staff
Administrative and technical staff positions are generally posted on the University of Toronto Careers website.
Teaching Assistantships (TAs) (CUPE 3902 Unit 1)
Teaching Assistant (CUPE3902 Unit 1) positions for Electrical & Computer Engineering courses only.
Eligibility
You must be a current or admitted U of T student or a postdoctoral fellow to be eligible.
Job postings
You can find TA job postings on the University of Toronto CUPE 3902 Unit 1 Job Posting Board.
- Fall-term courses: applications open in June, first round offers by mid-August
- Winter-term courses: applications open in October, first round offers by late November
Note: Emergency TA postings are posted throughout the year.
Application instructions
- Apply through the online TA Database (TAD) using your UTORid
- If you are an admitted graduate student you can use your JOINid
- Ensure you complete the Course Preferences section and upload a current Teaching resume in PDF format
- See Undergraduate Course Descriptions and Graduate Course Descriptions for course preferences
Note: TAs must complete the Teaching Assistant Training Program , FASE, AODA and Basic Occupational Health & Safety Training. See details on the Information for Current TAs page.
Course Instructors (CUPE 3902 Unit 1)
Eligibility
You must be a current or admitted U of T student or a postdoctoral fellow to be eligible.
Job postings
You can find CI job postings on the University of Toronto CUPE 3902 Unit 1 Job Posting Board.
Application instructions
Follow the instructions found on the job posting site.
Sessional Lecturers (CUPE 3902 Unit 3)
Sessional Lecturer (CUPE3902 Unit 3) positions for Electrical & Computer Engineering only.
Eligibility
The eligibility criteria are determined on a position-by-position basis. Check the posting of the position you are applying for.
Job postings
You can find Sessional Lecturer positions on the University of Toronto Careers page under CUPE 3902 (Unit 3) Opportunities.
Note: Positions may become available unexpectedly throughout the year.
Application instructions
- Complete Unit 3 Application Form (rtf)
- Complete up-to-date Teaching Resume
- Submit both to ugta.ece@utoronto.ca
If you require an accommodation during the application or selection process, please contact: ugta.ece@utoronto.ca.
Note: Applications will be retained for 24 months. If you have submitted an application and resume, you will receive emails for specific job postings during this 24-month period.
General information
This notice is posted pursuant to the CUPE Local 3902 Unit 3 Collective Agreement. Please note that in accordance with that agreement, preference in hiring is given to qualified persons advanced to the rank of Sessional Lecturer II or Sessional Lecturer III in accordance with Article 14:12.