Job Description

Date Posted: 08/13/2024
Req ID: 39278
Faculty/Division: Faculty of Applied Science & Engineering
Department: Inst for Aerospace Studies
Campus: St. George (Downtown Toronto)Description:Position: Sessional LecturerDepartment: Institute for Aerospace StudiesCourse number and title: ROB313H1S: Introduction to Learning from DataCourse description: This course will introduce students to the topic of machine learning, which is key to the design of intelligent systems and gaining actionable insights from datasets that arise in computational science and engineering. The course will cover the theoretical foundations of this topic as well as computational aspects of algorithms for unsupervised and supervised learning. The topics to be covered include: The learning problem, clustering and k-means, principal component analysis, linear regression and classification, generalized linear models, bias-variance tradeoff, regularization methods, maximum likelihood estimation, kernel methods, the representer theorem, radial basis functions, support vector machines for regression and classification, an introduction to the theory of generalization, feedforward neural networks, stochastic gradient descent, ensemble learning, model selection and validation.Posting End Date: September 4, 2024Number of Positions (est.): One (1) positionEstimated TA support: Two (2) TAsEstimated course enrolment: Approximately 72 studentsClass schedule: Tuesdays 3 - 6 pm & Fridays 3 - 5 pmHours: 1 HCE (up to a maximum of 230 hrs)Sessional dates of appointment: January 1 - April 30, 2025Salary: CUPE minimum salary rates for 0.65 half course (HCE), inclusive of vacation pay, are: Sessional Lecturer 1 - $5,518.29; Sessional Lecturer 1 Long Term - $5,765.01; Sessional Lecturer 2 - $5,905.63; and Sessional Lecturer 3 - $6,046.24. Should rates stipulated in the Collective Agreement vary from rates stated in this posting, the rates stated in the Collective Agreement shall prevail.Minimum Qualifications: include at least a Master\'s degree in Robotics or Computer Science, and an undergraduate degree in a robotics discipline such as computer engineering, control and mechatronics. An academic background in machine learning and computational/numerical methods studies is required. Knowledge in artificial intelligence, robotics and mechatronics is a further requirement. Strong knowledge of robotic sensing, control, and spatial perception is required. Knowledge of engineering mathematics with emphasis on complex variables and ordinary differential equations. Strong written and oral communication skills, a demonstrated commitment to teaching and demonstrated ability to work as part of a team.Preferred Qualifications: include experience as an instructor in Robotics or Computer Science, familiarity with the specific needs of ROB, and a strong working relationship with its faculty.Description of Duties:

• Preparing lectures
• Lecturing
• Setting exams
• Marking
• Providing support/feedback to students (individually and in groups)
• Recording and entering grades
• Ability to convert to online duties if required

Application Procedure:To apply please submit the following via email to Carmela Versace at : * Cover Letter

• CV/Resume

Late and/or incomplete applications will not be accepted/considered.Closing Date: 09/04/2024, 11:59PM EDT
**This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement.It is understood that some announcements of vacancies are tentative, pending final course determinations and enrolment. Should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II or Sessional Lecturer III in accordance with Article 14:12 of the CUPE 3902 Unit 3 collective agreement.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.All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.Diversity StatementThe 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 .Accessibility StatementThe 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 .

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