Research Associate (2 Year Term) - AI in Manufacturing

Date Posted: 07/22/2025
Req ID:44286
Faculty/Division: Faculty of Applied Science & Engineering
Department: Dept of Mechanical & Industrial Eng
Campus: St. George (Downtown Toronto)

Description:

AI in Manufacturing (AIM) is a research center funded under the Global Industrial Technology Cooperation Center (GITCC) program of Korea Institute for Advancement of Technology (KIAT). AIM is homed in the Department of Mechanical and Industrial Engineering at the University of Toronto and mandated to develop and manage R&D projects involving Korean private sector and Canadian Researchers. 

The Research Associate will work under the supervisor of Professor Chi-Guhn Lee, the Director of AIM, to develop new R&D projects by working with research institutes, firms and government offices in Korea, to manage and assist on-going projects homed in AIM, and to commercialize research outcomes from R&D projects completed or near completion. 

The Research Associate Term position will be responsible for:  

• Develop and execute research vision with PI to achieve research goals.
• Communicating with research institutes, firms and government offices in Korea.
• Processing and producing reports, proposals, and alike in English and in Korean.
• Managing and leading regular research meetings.
• Developing research proposals, conducting research, preparing presentations and publications where appropriate.
• Providing support with grant applications where appropriate.
• Provide technical support to R&D projects in the area of computing, AI and manufacturing.
• The Research Associate is expected to publish in journals and present at conferences.

Qualifications:

Education

• PhD degree in a STEM-related field (e.g., engineering, mathematics, computer science, or operations research) with demonstrated expertise in reinforcement learning and other AI related topics.

Experience

• Minimum three years of research experience in academia and minimum three years in industry on topics such as reinforcement learning, deep learning for image-based inspection and object detection after completing PhD studies.
• Experience in conducting data-driven research involving images, time-series, physical simulators, and transfer learning.
• Experience initiating and developing new R&D projects, including identifying research opportunities, defining objectives, and securing collaboration with relevant stakeholders.
• Cross-sector experience spanning private industry and research organizations will be seen as a significant advantage.
• Preference will be given to candidates with a strong record of creativity and innovation in AI, as demonstrated by patents.

Skills

• Fluent in Korean (verbal and written) where they must be able to collaborate with research partners in Korean and must be able to prepare and process government documents in Korean related to policies and regulations for R&D projects funded by the Korean government. 
• Fluent in English (verbal and written) to communicate with researchers and admin staff who can speak only English.
• Strong technical and analytical skills with solid understanding of reinforcement learning, transfer learning and time-series forecast.
• Strong technical writing and research communication skills in both academic and industrial contexts.
• Capable of managing multi-institutional R&D projects and facilitating collaboration between industry and academia.
• Proficient in deep learning frameworks such as PyTorch and TensorFlow.
• Demonstrable ability to apply initiative, tact, judgement, accuracy, and confidentiality with meticulous attention to detail.
• Intermediate skill level with MS Office Suite (Word, Excel, Outlook).
• Superior problem solving, customer service, and interpersonal skills with a demonstrated positive attitude and service orientation towards students, staff and the public.
• Proven capability to work independently, with instruction, and within a team environment.
• Proven ability to organize, multi-task, manage conflicting priorities and meet all deadlines while quickly adapting and learn new processes.
• Demonstrated commitment to equity, diversity, inclusion and the promotions of a respectful and collegial learning and working environment.

Note:

• This is a 2-year limited term position, with the possibility of renewal.

Closing Date: 08/26/2025,11:59PM ET
Employee Group: Research Associate 
Appointment Type: Grant - Term 
Schedule: Full-Time
Pay Scale Group & Hiring Zone: R01 -- Research Associates (Limited Term): $53,520 - $100,350
Job Category: Engineering / Technical