Sessional Lecturer - CSC2515HS - Introduction to Machine Learning

Job Title: Sessional Lecturer - CSC2515HS - Introduction to Machine Learning Company: University of Toronto Job Category: Machine Learning Roles & Responsibilities: Department: Dept of Computer Science Estimated TA support: support: 90 hours of TA support * Please note, the delivery method for this course is currently in\-person. Please note that, in keeping with current circumstances, the section delivery method may change as determined by the Faculty or the Department. Description of duties: * Preparing and delivering the lectures in\-person on campus as scheduled. * Handling course administration including: maintaining the course website on quercus; developing marking schemes/syllabus; planning tutorial content (when applicable); developing course assessments including assignments, projects, quizzes, tests, and final assessments. * Providing appropriate contact time outside of class to students, through office hours, email, the course website and/or the course bulletin board. * Preparing the breakdown of hours for TA duties in the course and supervising the TAs. * Ensuring that tutorials and/or labs are delivered appropriately by the TAs as applicable. * Managing the grading for the course, which is largely done by the TAs, and carrying out any grading not handled by the TAs. * Invigilating term tests and the final exam when applicable. * Managing the grades, including the timely completion and release of grades and feedback to students throughout the term; submitting final course grades (due May 8, 2026\). * This course will have a faculty supervisor; the successful candidate will be expected to liason with the faculty supervisor throughout the term with regular meetings to discuss topics such as: preparing course materials for the syllabus, lecture topics, and course assessments. While there is a lot of room for creativity in course delivery, instructors will be expected to follow the basic content and style used by the faculty members who normally teach the course, and must get approval from these faculty members or from the Associate Chair for any substantial changes to the course content or assessment methods. Instructors will also be expected to consult with the department’s Teaching Support group when creating the course syllabus and course assessments (tests, assignments, projects, and final exam) The University of Toronto has implemented a process to substantiate Indigenous Membership/Citizenship/Enrolment for candidates who identify as Indigenous. For more information about this process, please refer to the* Indigenous Substantiation Website.* Work Location: Toronto, Canada Availability: Full time

Machine learning (ML) is a set of techniques that allow computers to learn from data and experience, rather than requiring humans to specify the desired behaviour manually. This course introduces the main concepts and ideas in ML and provides an overview of many commonly used machine learning algorithms. It also serves as a foundation for more advanced ML courses. Reference: https://web.cs.toronto.edu/graduate/course\-descriptions\#csc2515s Salary: Minimum qualifications: * Doctoral degree in Computer Science or closely related field required. * Demonstrated expertise in topic area of the course required. * Strong organizational, interpersonal, and communication skills required. * Teaching experience at the university level or equivalent industry level required. Preferred qualifications: * Previous experience teaching undergraduate courses in the field of Computer Science preferred. 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. Please note: Undergraduate or graduate students and postdoctoral fellows of the University of Toronto are covered by the CUPE 3902 Unit 1 collective agreement rather than the Unit 3 collective agreement, and should not apply for positions posted under the Unit 3 collective agreement.* 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. 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. Job Segment: Computer Science, Training, Learning, Technology, Education, Human Resources Key Skills: Machine Learning Salary: CAD 14126 - 17441 per yearly