Training Lead (AI, AI for Science, Robotics, Lab Automation) at University of Toronto
Toronto, ON, Canada -
Full Time


Start Date

Immediate

Expiry Date

28 Sep, 25

Salary

0.0

Posted On

09 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Data Science, Instrumentation, Chemistry, Training, Machine Learning, Materials Science, Automation, Interpersonal Skills, Chemical Engineering, Robotics, Management Skills, Artificial Intelligence, Disabilities, Laboratory Automation, Consideration

Industry

Education Management

Description

Date Posted: 08/08/2025
Req ID: 42261
Faculty/Division: Faculty of Arts & Science
Department: Acceleration Consortium
Campus: St. George (Downtown Toronto)
Position Number: 00048987

ABOUT US:

Founded in 1827, the University of Toronto has evolved into Canada’s leading institution of learning, discovery and knowledge creation. We are proud to be one of the world’s top research- intensive universities, driven to invent and innovate. U of T is home to some of the world’s most
talented thinkers, inventors, innovators, and educators, who are advancing knowledge and making critical discoveries for a healthier, more sustainable, prosperous, and secure future.

ESSENTIAL QUALIFICATIONS:

  • PhD Degree in chemistry, materials science, chemical engineering, AI, data science, or physical or life sciences or an acceptable combination of equivalent education and experience.
  • Minimum of five years of recent and relevant experience planning post-secondary and industry/upskilling educational programs, course designs, and developing workshops for STEM subjects, including but not limited to machine learning, robotics, laboratory automation, and materials discovery.
  • Experience planning educational programs and course designs, and developing workshops
  • Experience conducting and disseminating peer-reviewed scientific research
  • Experience on training on the operation of instrumentation and experimental protocol
  • Experience in Chemistry, Material Sciences, Robotics, Artificial Intelligence, or the industrial adoption of AI or automation and related field
  • Excellent interpersonal skills and ability to collaborate on initiatives with a wide variety of contacts both internal and external to the University
  • Exceptional oral and written communication skills
  • Ability to handle conflicting and multiple priorities, superior organizational and time management skills
  • Ability to compile and analyze data, prepare reports and other informational materials
  • Proven analytical and problem solving skills and highly attentive to details

LIVED EXPERIENCE STATEMENT

Candidates who are members of Indigenous, Black, racialized and 2SLGBTQ+ communities, persons with disabilities, and other equity deserving groups are encouraged to apply, and their lived experience shall be taken into consideration as applicable to the posted position

Responsibilities

YOUR RESPONSIBILITIES WILL INCLUDE:

  • Building and strengthening relationships with stakeholders and partners of strategic importance and promoting the use of training resources through industry collaborations
  • Prepare and deliver training content as it relates to self-driving laboratories.
  • Planning components of educational programs and/or course design.
  • Developing content for instructional workshops and hackathons
  • Develop and deliver a faculty and student education engagement plan.
  • Planning and estimating financial resources required for educational programs.
  • Manage the delivery of the AC Micro-credentials program and other training content
  • High-school student outreach
  • Promoting the Acceleration Consortium’s training products

TO BE SUCCESSFUL IN THIS ROLE YOU WILL BE:

  • Accountable
  • Efficient
  • Entrepreneurial
  • Insightful
  • Multi-tasker
  • Organized
  • Persuasive
  • Possess a positive attitude
    This role is currently eligible for a hybrid work arrangement, pursuant to University policies and guidelines, including but not limited to the University of Toronto’s Alternative Work Arrangements Guideline.
    Closing Date: 08/29/2025, 11:59PM ET
    Employee Group: USW
    Appointment Type: Grant - Continuing
    Schedule: Full-Time
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