Sessional Lecturer CHE1148H: Process Data Analytics

Date Posted: 11/14/2024
Req ID: 40679

Faculty/Division: Faculty of Applied Science & Engineering
Department: Dept of Chemical Eng.& Applied Chemistry
Campus: St. George (Downtown Toronto)

Description: The driving force of the fourth industrial revolution is the processing and analysis of big data to extract knowledge, patterns and information. Chemical, biologics/pharma, oil/gas, financial and manufacturing organizations are in a unique position to benefit from this data revolution, as they collect and store massive amounts of heterogeneous data. Big data is characterized by the 5 V’s: volume, velocity, variety, veracity and value and distributed computing architectures are used to process the data. The first part of this course will be on Apache Spark, a big data processing and computing engine. In the second part, special topics in analytics such as visualization, data quality, interpretable/fair ML and MLOps will be discussed. Prerequisites: An introductory course in data science or machine learning (e.g. CHE1147 or other similar courses). Familiarity with Python.

Minimum Qualifications: Completion of an advanced degree (Master’s or Doctorate) in Chemical Engineering or related discipline is required. Candidates in progress of advanced degree completion (applies to non-University of Toronto graduate students) relevant professional experience and designations may also be considered. We are seeking candidates with strong written and oral communication skills and a demonstrated commitment to teaching. Candidates should have strong foundational knowledge of data process and data analytics. Previous experience in teaching, teaching excellence, and mastery of subject area. Previous experience in teaching a similar course is highly desirable.

Preferred Qualifications: In addition to the above minimum qualifications, successful applicants should have work experience in the chemical, biologics/pharma, oil/gas, financial and manufacturing industries.  

Duties: Developing a course syllabus, developing course materials (e.g., assignments, tests, exams), teaching three weekly one-hour class, conducting office hours, coordinating tutorials with TA assistance, marking assessments.

Closing Date: 11/20/2024, 11:59PM ET
Employee Group: CUPE 3902 (Unit 3)
Appointment Type: Sessional Lecuturer 

Schedule: Lecture Time: Wednesdays, 5:00 - 8:00 PM

Pay Scale Group & Hiring Zone: CUPE minimum salary rates for a half course (HCE), inclusive of vacation pay, are: Sessional Lecturer 1 - $9,457.90; Sessional Lecturer 1 Long Term - $9,930.79; Sessional Lecturer 2 - $10,121.77; Sessional Lecturer 2 Long Term - $10,326.62; Sessional Lecturer 3 - $10,362.76 and Sessional Lecturer 3 Long Term - $10,570.02. 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 Lecuturer

Application Procedure: Applicants should submit:

• Curriculum Vitae
• Unit 3 Application form

Please submit applications by email to ugradassist.chemeng@utoronto.ca with the following subject line: CHE1148 W25 Sessional Lecture Application.

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.