Les sécheresses extrêmes constituent un enjeu majeur dans un contexte de réchauffement climatique, affectant l’agriculture, les ressources en eau, la production énergétique et les écosystèmes. Leur caractère multi-échelle, dépendant des interactions entre précipitations, évapotranspiration, humidité du sol et stockage souterrain, rend leur détection et leur prévision complexes. Les indices traditionnels (SPI, SPEI, SSI) apportent une […]

This project focuses on developing and evaluating automated methods for analyzing complex no-code automation workflows used in enterprise environments. Platforms such as Workfront Fusion and Make.com allow organizations to build powerful automations quickly, but as these workflows grow in size and importance they often become difficult to understand, maintain, and safely modify. Changes are frequently […]

The main goal of this project is to integrate advanced machine learning techniques into the open-source PyBEST quantum chemistry software package to substantially accelerate quantum chemical calculations through the automated selection of optimal computational strategies. The project specifically targets the AI-driven optimization of tensor contraction operations (TCOs), which constitute the primary computational bottleneck in many […]

Le projet de recherche proposé vise à développer un système basé sur l’Intelligence Artificielle multimodale pour analyser à la fois les images morphologiques et les données génétiques de poissons appartenant aux espèces Diaphanus et Heteroclitus. L’objectif est de permettre l’identification automatique des espèces, de déterminer le sexe des individus et d’évaluer le degré d’hybridation afin […]

Intern(s) will help Thermweave develop washable fabrics that move heat away from the body with enhanced thermal conductivity. They’ll develop dip-coating recipes that use tiny carbon-based particles, dip common fabrics (cotton, polyester) in them, and fine-tune steps like time, temperature, and drying. The interns will test how well the fabric moves heat, and how it […]

This project will launch LigandQI, a next-generation Contract Research Organization (CRO) that empowers researchers in the pharmaceutical and biotechnology sectors with advanced molecular-interaction analysis. LigandQI applies state-of-the-art quantum chemistry and computational modeling to reveal, with exceptional precision, how drug candidates bind to their target proteins, enabling faster, more accurate lead optimization. Through the Lab2Market Launch […]

Frictive Pictures’ internship program will task its interns with documenting, composing, and promoting behind-the-scenes and educational content featuring the process of eight new voices in film as they create short films for broadcast and festival release. Interns will collaborate with industry professional producers to chronicle and create shareable content about the production process and then […]

Rapid urban growth challenges cities with rising populations, infrastructure demands, and environmental sustainability. Traditional urban planning, based on outdated models and fragmented data, struggles to address these complexities. Digital Twin (DT) technology offers a solution by creating dynamic virtual models of real-world environments using real-time data. By integrating sources like geographic information systems (GIS), sensors, […]

This project focuses on advancing computational methods for predicting ionization potentials (IPs) and electron affinities (EAs) of organic molecules, with a specific application to organic solar cells (OSCs). By leveraging Koopmans’ theorem within the orbital-optimized pair-coupled cluster doubles (oo-pCCD) framework, the project aims to efficiently compute these key electronic properties without costly gradient calculations. A […]

The rate and magnitude of environmental change present a threat to freshwater fish populations. In Atlantic Canada the impacts to the freshwater ecosystems will arise through elevated water temperatures, alterations in precipitation, variability in ice cover and frequency of natural and man-made disturbances. In addition, temporal and spatial changes to precipitation alter seasonal flow patterns […]

Deep learning systems can predict properties of chemical substances but do so in a purely mathematical way. As a consequence, the user does not get any feedback on what are the essential properties a chemical must have to exhibit a certain property. This hampers getting any insight in to the relationship between molecular structure and […]

Through a current co-op project, International Game Technology (IGT) and the University of New Brunswick are developing a powerful artificial intelligence (AI) model to predict the performance of Video Lottery Terminal (VLT) games. However, the model currently functions as a “black box,” making it difficult for business teams like game designers to trust its recommendations […]