Date Posted: 06/02/2024
Closing Date: 06/24/2024, 11:59PM ET
Req ID: 37658
Job Category: Sessional Instruction
Faculty/Division: Faculty of Applied Science & Engineering
Department: Dept of Mechanical & Industrial Eng
Campus: St. George (Downtown Toronto)

Description:

Description: The objective of the course is to learn analytical models and overview quantitative algorithms for solving engineering and business problems. Data science or analytics is the process of deriving insights from data in order to make optimal decisions. It allows hundreds of companies and governments to save lives, increase profits and minimize resource usage. Considerable attention in the course is devoted to applications of computational and modeling algorithms to finance, risk management, marketing, health care, smart city projects, crime prevention, predictive maintenance, web and social media analytics, personal analytics, etc. We will show how various data science and analytics techniques such as basic statistics, regressions, uncertainty modeling, simulation and optimization modeling, data mining and machine learning, text analytics, artificial intelligence and visualizations can be implemented and applied using Python. Python and IBM Watson Analytics are modeling and visualization software used in this course. Practical aspects of computational models and case studies in Interactive Python are emphasized.

Estimated course enrolment: TBD

Estimated TA support: TBD

Class schedule: TBD

Sessional dates of appointment: September 2024 – December 2024

Salary: $15,000 (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 Manager, Academic Programs by email at carla@mie.utoronto.ca  no later than June 24, 2024 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 Carla Baptista at carla@mie.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. 

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 encourage to apply; however, Canadians and permanent residents will be given priority.

All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.

Diversity Statement
The 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 http://uoft.me/UP.

Accessibility Statement
The 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 uoft.careers@utoronto.ca.