Research project title
AI-Driven Multi-Scale Modeling and Digital Twin Development for Advanced Manufacturing Systems
Education level
Post-doctoral fellowship
Director/co-director
Director: Farbod Khameneifar
End of display
March 31, 2026
Areas of expertise
Materials science and technology
Primary sphere of excellence in research
Industry of the Future and Digital Society
Secondary sphere(s) of excellence in research
Modeling and Artificial Intelligence
Unit(s) and department(s)
Department of Mechanical Engineering
Digital manufacturing and metrology (DMM) research laboratory
Detailed description
A postdoctoral position is available as part of a new research project conducted in collaboration with industrial partners.
The project aims to develop advanced numerical models and AI-based approaches for predicting and optimizing the behavior of complex systems in manufacturing contexts. The work will focus on multiscale modeling, integration of experimental data, parameter identification, and the development of digital twins that combine physics-based modeling and machine learning.
Responsibilities
Develop multi-scale numerical models
Integrate experimental data into computational models
Develop parameter identification and model calibration approaches
Implement machine learning and surrogate modeling approaches
Participate in validation and industrial demonstration activities
Publish results in international scientific journals
Required Profile
PhD in Mechanical Engineering or related field
Strong background in numerical modeling or computational mechanics
Experience in simulation (finite elements, etc.)
Knowledge of artificial intelligence and machine learning
Experience with Python, MATLAB, or equivalent environments
Ability to work independently and in collaboration with industrial partners
Conditions
Duration: 12 months (renewable depending on funding)
Start date: Flexible
Competitive salary according to Canadian standards
Access to high-performance computing resources
Dynamic research environment with industrial collaborations
Interested candidates should send:
- Detailed CV
- List of publications
- Brief statement of research interests
- Contact information for two referees
to: Prof. Farbod Khameneifar
Financing possibility
Funding for the position is secured for an initial 12-month period, with the possibility of renewal depending on project progress and available funding.
