Research project title
Developing a Semantic Integration and Consistency Framework for Hierarchical Digital Twins
Education level
Doctorate
Director/co-director
Director: Bentley Oakes
Co-director(s): Jean-Marc Frayret, Yasmina Maïzi
End of display
December 1, 2025
Areas of expertise
Adaptive, learning and evolutionary systems
Intelligent systems applications
Modelling and simulation studies
Virtual reality and related simulations
Unit(s) and department(s)
Department of Computer Engineering and Software Engineering
Conditions
QUALIFICATIONS:
Highly motivated candidates with the following qualifications are sought:
- Master’s degree in software engineering, or applied mathematics, or with relevant experience,
- Excellent written and verbal communication skills in English and/or French,
- Motivation to learn and solve problems,
- Ability to work with diverse academic and industrial teams,
- Prior experience in one or many of the following fields is a plus: modelling and simulation, ontological reasoning, digital twin construction.
Please see my lab page for details on applying: https://bentleyjoakes.github.io/lab/
Under-represented candidates are especially encouraged to apply.
DURATION OF STUDIES:
Four years for doctoral studies.
APPLICATION DEADLINE:
The candidate search will continue until the positions are filled. Please see https://www.polymtl.ca/admission/en/graduate-studies/check-application-deadlines.
STARTING DATE:
September 2025, or as soon as possible.
LANGUAGE:
Note that the research will take place in English, though the candidate will have to take graduate courses in French.
Detailed description
The project concerns Electric Air Mobility (EAM) such as VTOL drones, and their interconnections with Digital Twins (DT). The objective is to create a structural semantic backbone for orchestrating interactions between DTs of the EAM ecosystem at different hierarchical levels, which can be distinguished as: unit, process, system, and finally system-of-systems DTs. The challenge is to integrate DT models at each level, and also ensure robust and consistent interactions between levels. To this end, it is necessary to improve the ability of systems, processes and units to exchange/communicate/operate together at the semantic level, thus ensuring interoperability and coherence throughout the EAM ecosystem.
The candidate will develop theoretical and practical knowledge/skills in:
- Digital Twin construction and evolution
- Monitoring of data consistency, requirement verification, and model validity
- Semantic technologies such as ontological and meta-modelling
Financing possibility
Full funding available
