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You must apply through WORKDAY. For detailed instructions, click on the appropriate link below.

For External candidates (not a current employee at McGill) see the instructions HERE / (Français)

For Internal candidates (currently employed at McGill - you must be connected to the VPN), see the instructions HERE / (Français)

 

The Department of Mining and Materials Engineering is inviting applications for the following Winter 2026 Course Lecturer Positions

Deadline to apply: October 15, 2025 @ 11:59 pm (the posting will expire at midnight)

Salary: $11,479

 

MIME 341 – Introduction to Mineral Processing (Laboratory Section) – Winter 2026

Overview: Theory and practice of unit operations including size reduction-crushing and grinding; size separation-screening and classification; mineral separation-flotation, magnetic and gravity separation. Equipment and circuit design and selection. Mass balancing. Laboratory procedures: grindability, liberation, magnetic and gravity separation, flotation and solid-liquid separation.

Teaching Qualification Requirements:

Education: Graduate level training in mineral processing with PhD preferred

Experience: Hands-on experience setting up and teaching mineral processing in a laboratory setting

Additional Information: Professional Engineering Licence, P.Eng., preferred

 

MIME 473 Introduction to Computational Materials Design

Overview: Introduction to modelling and simulation techniques in materials engineering: quantum mechanics and atomistic simulation (i.e. Monte-Carlo and Molecular Dynamics). These modelling and simulations methods provide new and efficient tools to examine and predict various physical and mechanical properties of materials, enabling bottom-up design of materials and structures starting from quantum and atomistic level. These computational tools play an increasingly important role in modern materials engineering. Fundamental theories behind materials modelling and hands-on training on various modelling software.

Teaching Qualification Requirements:

Education: PhD with training in the field of computational materials science preferred. In exceptional cases, PhD students may be considered.

Experience: Proficiency in atomistic-scale modeling and python or C/C++ programming required. Prior teaching experiences (including teaching assistant experiences) on MIME 473 or equivalent courses preferred.

Additional Information: Strong communication skills. P.Eng. Preferred. Knowledge of atomistic-scale modeling and molecular dynamics simulations.

 

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