Research Intern – AI-Numerical Modelling Sustainable Mining, School of Engineering and Computer Science

Position No.: JOBPOST-

Salary: $39,960 per year

Competition ends: Tuesday, October 27th at 4:30 pm

Grant appointment until December 31, 2027

This position is designated as one that requires a variable work schedule. However, it is understood that your work week will consist of 35 hours.

This opportunity is proudly supported by Northern Ontario Heritage Fund Corporation and is funded through the Workforce Development Program. Eligibility requirements of the program can be found here:
Workforce Development Program - Home | NOHFC

The Research Intern will contribute to an applied research project focused primarily on numerical modelling of tire-road interaction and tire-induced microplastic generation under underground mining conditions. Approximately 80% of the research will involve numerical modelling using appropriate numerical modelling software, such as the ITASCA software suite, particularly Particle Flow Code (PFC). The study will focus on a limited and logically selected set of representative mining conditions that can reasonably be investigated within the oneyear internship.

The intern will develop and calibrate numerical models, conduct selected parametric simulations, and analyze the resulting data. Artificial intelligence and machine-learning methods may be used as a supporting component and are expected to represent no more than approximately 20% of the research work.

• Develop and calibrate numerical models of tire-road interaction, tire wear, and particle detachment under underground mining conditions using appropriate numerical modelling software, such as the ITASCA software suite, particularly Particle Flow Code (PFC).
• Conduct numerical simulations for a limited and logically selected set of representative mining conditions and parameters appropriate to the one-year project duration.
• Analyze simulation results and identify the main parameters affecting tire wear and tire-induced particle generation.
• Organize selected simulation results into a structured dataset and, where appropriate, apply limited artificial intelligence or machine-learning methods to support prediction and interpretation. AI-related activities will represent no more than approximately 20% of the overall research work.
• Document the numerical modelling methodology and results and contribute to technical reports, presentations, and research publications.

• Master's degree in Mining Engineering, Rock Mechanics, Geotechnical Engineering, Geological Engineering, Civil Engineering, Structural Engineering, or a closely related field with relevant numerical modelling experience.
• Demonstrated experience in numerical modelling of mining, rock mechanics, geomechanics, geotechnical, or closely related engineering problems is mandatory.
• Experience with numerical modelling software applicable to mining, rock mechanics, geomechanics, or related engineering problems is required. Experience with the ITASCA software suite, particularly Particle Flow Code (PFC), is considered an asset. Applicants from other disciplines must also demonstrate relevant numerical modelling experience in rock mechanics, geomechanics, or related engineering applications.
• A minimum of one(1) year of relevant research or technical experience involving numerical modelling of mining, rock mechanics, geomechanics, geotechnical, or closely related engineering problems.
• Experience obtained through a master's thesis, graduate research, research assistantship, or relevant professional work may be considered. Experience with Particle Flow Code (PFC), Fast Lagrangian Analysis of Continua (FLAC), or other ITASCA numerical modelling…