Algebraic Structures in Quantum Non-Local Games

This 12-week research internship at the University of Ottawa hosts an MSc student from ENS Paris-Saclay, advancing research in mathematical aspects of quantum information. The project studies how algebraic structure and symmetry can simplify and certify quantum behaviours in non-local games, a core tool for device-independent cryptography. By translating game rules into algebraic objects and […]

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Graph Neural Networks for Wind Power Modelling

This project aims to develop new machine learning models that can help wind energy companies design wind farms more efficiently and at lower cost. Today, planning a wind farm requires running large, high-resolution computer simulations to understand how wind flows around turbines and how much power a proposed layout can produce. These simulations are accurate […]

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Mathematical Models of Oncolytic Virotherapy Including Oxygen Dependent Phenotypic Adaptation

This project develops mathematical models to investigate how tumour heterogeneity and oxygen availability influence the efficacy of oncolytic virotherapy (OVT). OVT employs genetically engineered viruses to selectively infect and destroy cancer cells, yet its therapeutic success is often hindered in hypoxic tumour regions, where low oxygen levels promote cellular adaptations that reduce viral replication and […]

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Generalized Thermodynamically Admissible 13-Moment Equations

This project explores how to better model gas flows in situations where traditional fluid equations break down, such as in very small systems or low-pressure environments. Instead of relying on costly molecular simulations, the research develops advanced extensions of classical fluid models that remain mathematically stable and thermodynamically consistent, while being flexible enough to describe […]

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Integration of traditional and telematics data via mass imputation

While telematics data with measurements of specific driving behaviors such as speeding, breaking, and turning, have shown significant predictive power in modeling accident risk, its usability has been challenged due to the low proportion of auto insurance policyholders that agree to provide their telematics data to the insurance companies. In this regard, we propose a […]

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Détection, prévision et interprétabilité des sécheresses extrêmes à l’aide de l’intelligence artificielle

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 […]

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L2M – GradientX

Nowadays, many young Canadians [2] and newcomers [1] begin their financial journey with limited access to guidance on saving and investing, which leaves them at risk of debt and missed opportunities to build wealth. Existing tools are often complex and designed for experienced investors, not beginners. This project aims to develop and validate GradientX, an […]

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Ordonnancement multi-objectifs des projets comptables

Beeye développe des algorithmes avancés d’optimisation automatisée des tâches, spécialement conçus pour résoudre des problématiques complexes liées à la gestion des ressources. Ses activités principales comprennent la création d’un système de planification automatisé qui s’attaque au problème de la planification multi-objectifs sous contraintes (MORCPSP). Ce système permet de gérer efficacement l’allocation des ressources, tout en […]

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New Perspectives in Quantum Materials: Floquet Circuits and Magnetic Aspects of Hyperbolic Lattices

This project aims to develop new driving protocols and investigate the exotic physical properties of hyperbolic quantum materials using time-periodically modulated (“Floquet”) electrical circuits under magnetic driving. By leveraging these programmable circuits, we will explore how curvature and periodic modulation influence energy flow, spectral features, and effective magnetic behavior in synthetic hyperbolic lattices. The collaboration […]

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Integrating large-scale data sources, Generative AI and Large Language Models (LLMs) in advanced NLP-based techniques and quantitative models.

Picton Mahoney Asset Management (“PICTON Investments”) was founded in 2004 to provide unique investment solutions to institutional, retail, and high-net-worth investors in Canada and globally. The Quantitative Research and Risk team at PICTON Investments is dedicated to developing and maintaining models that support investment decisions and risk assessments. With the increasing complexity of financial markets […]

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