Contract Instructor Teaching Opportunities (Late posting)
Department of Systems and Computer Engineering
Winter 2027
Contract Instructor Salaries for Fall 2026 and Winter 2027 courses:
Half Credit Course: $9,255
Full Credit Course: $18,508
Pursuant to Article 16.3 of the CUPE 4600 Unit 2 Collective Agreement, subject to Article 16.2 and 16.4 through 16.7, applications are invited from members of the CUPE 4600 bargaining unit and other interested persons to teach the following courses in the Winter 2027 terms.
Carleton University is committed to employment equity and fostering a culture of inclusion. We encourage applications from individuals who would contribute to the diversity of our campus, including women, visible minorities, First Nations, Inuit, and Métis peoples, persons with disabilities, and persons of any sexual orientation or gender identity and expression. Applicants requiring accommodations at any stage of the recruitment process are encouraged to contact the Department Chair at SCEChair@cunet.carleton.ca to ensure appropriate arrangements can be made in a timely manner.
Required Qualifications:
Candidates should have excellent communication and presentation skills; strong teaching skills established through successful teaching of engineering courses in an accredited Canadian university engineering program; and a high level of up-to-date expertise in the subject of the course, established through industrial experience and/or research in academia or government labs. Candidates must have a degree in a relevant field of engineering. A P.Eng. license in Canada is required for the instruction of most undergraduate courses.
The modality of the courses is determined by the University. The courses listed are in-person. In the event, public health authorities impose public health restrictions, part or all of the courses may need to be delivered online as required by the University and as directed by public health authorities.
Required Academic Qualifications and Skills: Depending on the course, candidates should hold a Masters or Ph.D. in the area of Computer Engineering, Software Engineering, Electrical Engineering or the equivalent.
Required Professional Qualifications and Skills: Candidates may be required to be a Licensed Professional Engineer (P.Eng.). Please contact the department for details.
Teaching Competence: Candidates are required to have experience teaching. Candidates are also asked to provide a brief explanation of how their educational qualifications and professional experience position them for success as a teacher for the course(s), as qualification/experience relates to the course description(s) (see course descriptions here).
Posting Information
| Posting Date | September 24, 2026 |
|---|---|
| Application Deadline | October 15, 2026 |
| Application Page | Application Form |
| Posting Type (regular/Late) | Late |
When applying to classes for which they have incumbency, applicants shall not be required to (re)submit documentation beyond their updated CV. With one (bundled) file using the following name convention: LastName-FirstName CI-Application.zip, your application must include the following:
- CV
- Cover letter indicating your teaching experience and expertise as it relates to the course(s)
Note: The SCE Department does not use artificial intelligence (AI) tools at any stage of the hiring process.
To view course offerings and times for Fall 2026 and Winter 2027, please refer to the public class schedule here, when available.
Click on the course number to view description.
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- Course number: SYSC 4106
- Course title: Algorithms and Data Structures
- Term: Winter 2027
- Course description: Thorough coverage of fundamental abstract collections: stacks, queues, lists, priority queues, dictionaries, sets, graphs. Data structures: review of arrays and linked lists; trees, heaps, hash tables. Specification, design, implementation of collections, complexity analysis of operations. Sorting algorithms.
- Course credit value: 0.5
- Anticipated modality: In-Person
- Anticipated Course Enrolment: 100
- Anticipated TA Support*: 1 TA @ 130 hours
- Required qualifications: See above
-
- Course number: SYSC 4106
- Course title: The Software Economy and Project Management
- Term: Winter 2027
- Course description: Introduction to software project management and economics; Return on software investments; Software life cycle; Work breakdown structure, scheduling and planning; Risk analysis and management; Product size and cost estimation; Earn value management; Statistical process control; Managing project team and process improvement; Bidding and contract types.
- Course credit value: 0.5
- Anticipated modality: In-Person
- Anticipated Course Enrolment: 120
- Anticipated TA Support*: 1 TA @ 130 hours
- Required qualifications: See above
-
- Course number: SYSC 4120
- Course title: Software Architecture and Design
- Term: Winter 2027
- Course description: Introduction and importance of software architectures and software system design in software engineering. Current techniques, modeling notations, methods, processes and tools used in software architecture and system design. Software architectures, architectural patterns, design patterns, software qualities, software reuse.
- Course credit value: 0.5
- Anticipated modality: In-Person
- Anticipated Course Enrolment: 100
- Anticipated TA Support*: 1 TA @ 130 hours
- Required qualifications: See above
-
- Course number: SYSC 4700
- Course title: Topics in Communications Networks
- Term: Winter 2027
- Course description: Contemporary and emerging topics in communications networks and technologies. Communications as a national and international infrastructure. Systems view of network architecture and management: transmission, access, interference, routing, softwarization, virtualization, security. Regulations and standards. Examples include cellular 5G/6G, Wi-Fi, terrestrial, optical, aerial, and satellite networks.
- Course credit value: 0.5
- Anticipated modality: In-Person
- Anticipated Course Enrolment: 100
- Anticipated TA Support*: 1 TA @ 130 hours
- Required qualifications: See above
The following courses have been assigned to doctoral students, postdoctoral fellows, or visiting scholars, and therefore are not open for applications.
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- Course number: SYSC 4415
- Course title: Introduction to Machine Learning
- Term: Winter 2027
- Course description: Introduction to supervised and unsupervised machine learning (ML), including deeper knowledge of several algorithms of each type. Evaluation and quantification of predictive performance of ML systems. Use of one or more ML development environments.
- Course credit value: 0.5
- Anticipated modality: In-Person
- Anticipated Course Enrolment: 100
- Anticipated TA Support*: 1 TA @ 130 hours
- Required qualifications: See above
-
- Course number: SYSC 4416
- Course title: Artificial Intelligence in Engineering
- Term: Winter 2027
- Course description: Fundamental ideas and techniques underlying the design of intelligent computer systems. Topics include intelligent agents, problem solving by searching, uncertain knowledge and reasoning, introduction to machine learning, and selected AI applications. A special focus is given to engineering use cases and applications of AI.
- Course credit value: 0.5
- Anticipated modality: In-Person
- Anticipated Course Enrolment: 100
- Anticipated TA Support*: 1 TA @ 130 hours
- Required qualifications: See above
*Please note that anticipated TA support is based on anticipated enrollment and may change based on actual enrollment in a course
A note to all applicants: As per Articles 16.3 and 16.4 in the CUPE 4600-2 Collective Agreement, the posted vacancies listed above are first offered to applicants meeting the incumbency criterion. A link to the current CUPE 4600-2 Collective Agreement can be found at the Employment Agreements webpage on the Carleton University Human Resources website and the CUPE 4600-2 website.
For more information, please contact the Department Administrator at SCEDeptAdmin@cunet.carleton.ca