Most computers and materials work on scales such that quantum effects can be comfortably ignored. But as we aim to make computers ever smaller, quantum effects will cause difficulties; however, they also provide opportunities. Spin-crossover (SCO) materials are molecules that can “Flip” between two states: either high or low spin binary states, making them essentially […]

La prévision de la demande d’électricité à court terme est un des enjeux majeurs de l’exercice des activités d’Hydro-Québec. Cette tâche requiert de calibrer les paramètres de modèles de prévision complexes par rapport à un grand nombre de données. Or, un des systèmes de calibration utilisé quotidiennement éprouve des difficultés d’adaptation face à la nouvelle […]

This proposal is devoted to two areas of sheep production: animal health (parasitic infection) and feed efficiency, which both impact profitability and sustainability. We will investigate potential machine learning using biomarkers indicating parasite resistance and feed efficiency in differentiated animals early in life. One postdoctoral fellow (PDF) will use metabolomics, genomics, and machine learning to […]

Au cours des dernières années, la recherche en reconnaissance gestuelle a connu une forte effervescence, principalement appuyée sur la démocratisation de l’intelligence artificielle. Cependant, les approches actuelles rencontrent souvent des défis en termes de robustesse et demandent un grand effort de calibration. Pour remédier à ces limitations, ce projet propose d’employer la fusion de signaux […]

The proposed project aims to enhance the interpretability of machine learning models, particularly in the context of time series data analysis. By extending the capabilities of the tsfresh library, a widely used tool for time series feature extraction, the project seeks to make complex models more transparent and understandable. This effort will improve confidence in […]

Ultrafast electron diffraction (UED) is an established tool to record atomic motion on very short timescales well below one picosecond. The sample, typically less than 100 nanometers thick, is first excited with an optical pump-pulse leading to the rearrangement of its atomic or molecular constituents. Subsequently, the structural changes are probed by a short electron […]

This research project aims to significantly improve the way data are managed in a specific self-driving laboratory in the AUTODIAL group of Prof. Hattrick-Simpers at the University of Toronto, focusing on discovering new materials that are resistant to corrosion. This class of labs, known as Self-driving labs (SDL) or Materials Acceleration Platforms (MAPs), use advanced […]

The project between Plato Testing Inc. and NBCC has been built to support indigenous students of the software testing program to gain industry experience and utilize the skills they have developed in class. The software testing industry is ever growing, and requires talented students with an understanding of programming and software development to make software […]

Semiconducting polymers (SPs) are at the forefront of the next generation of organic electronics. They enable seamless integration into various biological and industrial applications. SPs can be engineered to be mechanically compliant and soft, giving them an advantage over silicon-based electronics. Their electronic and solid-state properties also make them promising candidates for emerging organic electronics. […]

Le présent projet répond à la nécessité de développer des outils visant l’autonomisation et l’amélioration de la santé générale des jeunes atteints de pathologies chroniques. À cet effet, la plateforme Inpowr est un espace web qui permet de jauger son bien-être personnel par l’entremise de questions générales, de se fixer des buts précis, des comportements […]

In this project, we explore using augmented reality avatars for supporting learning in low-traffic makerspaces. While makerspaces primarily provide community members with access to tools, they also serve as places to learn where community members build expertise with the equipment and fabrication processes. This learning process can either be guided formally using the makerspace as […]

Wind energy technology plays a crucial role in the global strategy for a green transition, with a significant acceleration in deploying new wind power plants being essential to meet global CO2 reduction targets. In this context, research in numerical simulation can provide the renewable energy sector with reliable tools for new wind farm design, land […]