Date Posted: 07/08/2025
Req ID: 44043
Faculty/Division: Faculty of Applied Science & Engineering
Department: Dept of Chemical Eng.& Applied Chemistry
Campus: St. George (Downtown Toronto)
Description: Artificial Intelligence (AI) and Data Informed Decision Making (DIDM) rely heavily on data and the use of AI and DIDM is necessary in order to maintain competitiveness in modern manufacturing. Industry benchmarks indicate that 70-80% of the effort in implementing AI and DIDM is associated with the task of acquiring pertinent data. Organizing and thereby making industrial data easier to acquire would help mitigate the efforts involved. This course introduces the current tools and concepts used to address this problem. Students will learn about Industry standards, approaches, and data transport protocols. Working both in team and individual environments, these concepts will be applied to real world scenarios.
Minimum Qualifications:
A BEng or BASc degree in Chemical Engineering, 5 years of experience in data analytics and artificial intelligence in an industrial setting
Preferred Qualifications:
Professional Engineer
Duties:
Develop course syllabus, deliver lectures, mark exams, supervise project teams
Closing Date: 07/16/2025, 11:59PM ET
Employee Group: CUPE 3902 (Unit 3)
Appointment Type: Sessional Lecturer
Schedule: Lecture Time: September 2, 2025 - December 31, 2025; Mondays, 11:00 AM - 2:00 PM
Pay Scale Group & Hiring Zone: CUPE minimum salary rates for a half course (HCE), inclusive of vacation pay, are: Sessional Lecturer 1 - $ 9,820.70; Sessional Lecturer 1 Long Term - $ 10,510.03; Sessional Lecturer 2 - $10,510.03; Sessional Lecturer 2 Long Term - $10,760.27; Sessional Lecturer 3 - $10,760.27 and Sessional Lecturer 3 Long Term - $11,030.35. Should rates stipulated in the Collective Agreement vary from rates stated in this posting, the rates stated in the Collective Agreement shall prevail.
Job Category: Sessional Lecturer
Application Procedure: Applicants should submit:
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