CALL Impact+ Research Chairs

Position: Copy of CALL FOR APPLICATIONS Impact+ Research Chairs (75447)
Location: Trois-Rivières

Posted from February 23 to March 26, 2026

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Canada Impact+ Research Chairs
The Université du Québec à Trois-Rivières (UQTR) is seeking applications from researchers for the 2026 CANADA IMPACT+ RESEARCH CHAIRS competition on the theme of cognitive systems applied to smart manufacturing.  The digital transformation of the manufacturing sector is an essential lever for economic competitiveness, industrial sovereignty, and the transition to a sustainable economy.  The integration of advanced technologies — including artificial intelligence, cyber‑physical systems, digital twins, the Industrial Internet of Things, and automation — is profoundly redefining production and decision‑making methods.  

It is enabling the emergence of interconnected, adaptive, and autonomous industrial systems capable of responding to market volatility and supply chain complexity.  This evolution, combined with the smart industry paradigm, aims to create interconnected, adaptive, and autonomous production systems capable of responding to the demands of volatile markets and complex supply chains.  In this context, cognitive systems represent a decisive step forward.  

They equip industrial infrastructures with the ability to perceive, learn, reason, and act autonomously or collaboratively with humans.  By combining artificial intelligence, advanced analytics, knowledge modeling, and intelligent robotics, they transform the factory into a socio‑technical system where humans and machines cooperate in hybrid decision‑making loops.  This evolution goes beyond traditional automation by introducing capabilities for adaptation and anticipation.

Cognitive systems enable real‑time optimization of industrial processes.  Through continuous analysis of data from sensors and equipment, they dynamically adjust production parameters, improve quality, reduce losses, and optimize energy consumption.  They also support augmented decision‑making by simultaneously evaluating multiple scenarios and providing explainable recommendations to operators.

They also contribute to fault prediction and industrial resilience.  By detecting anomalies and signs of deterioration early on, they enable predictive and prescriptive maintenance, limiting unplanned downtime and extending equipment life.  In addition, they ensure the intelligent orchestration of distributed production systems, coordinating resources, flows, and planning in interconnected industrial networks.  These transformations simultaneously improve industrial productivity, flexibility, and sustainability.  Cognitive systems promote resource efficiency, waste reduction, and energy optimization, contributing to the circular economy and reducing carbon footprints.  

They also facilitate the rapid adaptation of production lines to new products or volumes, strengthening the competitiveness of businesses.

For Canada, the development of smart manufacturing is part of national strategic priorities such as productivity, technological sovereignty, energy transition, critical infrastructure security, and sustainable development.  Strengthening capabilities in industrial cognitive systems can thus position the country as a leader in smart industry while modernizing its manufacturing value chains.

Several major challenges remain.  It is necessary to design robust, explainable, and secure cognitive systems for critical industrial environments.  The integration of artificial intelligence into cyber‑physical systems requires new architectures and engineering methods that guarantee reliability and security.  Human‑machine collaboration raises issues of ergonomics, trust, skills, and work organization.  The management of massive, heterogeneous, and sensitive industrial data requires sovereign and interoperable infrastructures.  

Finally, cybersecurity and the resilience of smart industrial systems are becoming priorities in the face of increasing connectivity.  The transformation of manufacturing also involves organizational challenges related to the orchestration of digital industrial ecosystems.  It requires close collaboration between companies, research centres, and public institutions, as well as…