CHE1149H: Chemical Engineering Data Organization
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.
Responsibilities
- Developing a course syllabus and course materials (e.g., assignments, tests, exams).
- Instructing / teaching, and testing.
- Conducting office hours.
- Coordinating tutorials with TA assistance.
- Marking / grading assessments (quizzes, tests, assignments, exams).
- Providing constructive feedback to students.
Qualifications
Minimum: A BASc degree in Chemical Engineering, five years of experience in data organization.
Preferred: 10 years of experience in data organization.
Schedule
September 1, 2026 – December 31, 2026. Monday 10:00 AM – 1:00 PM.
Pay
CUPE minimum salary rates for a half course (HCE), inclusive of vacation pay, are:
- Sessional Lecturer 1 – $9,997.48
- Sessional Lecturer 1 Long Term – $10,699.22
- Sessional Lecturer 2 – $10,699.22
- Sessional Lecturer 2 Long Term – $10,953.96
- Sessional Lecturer 3 – $10,953.96
- Sessional Lecturer 3 Long Term – $11,228.90
Should rates stipulated in the Collective Agreement vary from rates stated in this posting, the rates stated in the Collective Agreement shall prevail.
Application Procedure
Applicants should submit Curriculum Vitae and Unit-3-Application by email to ugradassist.chemeng@utoronto.ca with the subject line: CHE1149H Sessional Lecture Application.