MIE1628H: Cloud-Based Data Analytics (formerly Big Data Science)
Toronto, ON, CA
University of Toronto
The University of Toronto is a globally top-ranked public research university in Toronto, Ontario, Canada.Date Posted: 03/17/2025
Req ID: 42202
Faculty/Division: Faculty of Applied Science & Engineering
Department: Dept of Mechanical & Industrial Eng
Campus: St. George (Downtown Toronto)
Description:
Job Posting: March 17, 2025, Job Closing: April 4, 2025, 11:59PM EDT.
Description: This course covers Big Data fundamentals including an overview of Hadoop MapReduce and Spark. Covers Cloud fundamentals and Big Data Analytics on Cloud-based platforms including an introduction to a specific Cloud platform such as Microsoft Azure, Amazon Web Services, or Google Cloud Platform along with common practices for this platform. Covers Cloud technologies to store and process structured, unstructured and semi-structured data. Covers Cloud-based implementation of Real-time Analytics and Machine Learning.
Estimated course enrolment: TBD
Estimated TA support: TBD
Class schedule: TBD
Sessional dates of appointment: May 2025 –August 2025
Salary: $30,000 (per half course inclusive of vacation pay) per section. Please note that 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: Applicants should have a strong record of presenting lectures or acting as a teaching assistant. Applicants must be able to demonstrate considerable depth of knowledge and experience in the subject area. The applicant must have excellent communication skills in both oral and written.
Description of duties: Preparation of lectures and course materials; delivery of lectures; supervision of Teaching Assistants; setting and marking of projects, tests and exams; evaluation of final grades; contact with students.
Application instructions: Please submit a Course Instructor Application Form, Resume and Teaching Dossier to the MIE Graduate Administrator by email to jonathan.alexander@utoronto.ca no later than April 4, 2025 at 11:59pm (Eastern Time). The Course Instructor Application Form can be found on the MIE Careers page at: https://www.mie.utoronto.ca/faculty-staff/careers/
If during the application and/or selection process you require accommodation due to a disability, please contact MIE Graduate Administrator by email to jonathan.alexander@utoronto.ca.
The appointment will be made at the earliest possible time before the commencement of classes by the Associate Chair (Graduate) of the Department of Mechanical and Industrial Engineering. No other offers or notices of the outcome of applications are authorized by the Department. Final availability of the position is contingent upon final course determination, enrolment, budgetary considerations, and the final determination of assignments flowing from Article 14:03 of the Collective Agreement.
This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement.” And “Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II and Sessional Lecturer III in accordance with Article 14:12.”
Closing Date: 04/04/2025, 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.
Tags: AWS Azure Big Data Data Analytics Engineering GCP Google Cloud Hadoop Industrial Machine Learning Spark Teaching
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