Pollution control of gas mixtures: gas monitoring and detection of contaminants usingnovel THz technology Year Two

Electric power plants are the number one toxic air polluters in North America. The emitted pollutants are proven to cause serious health and environmental issues. The emission of Carbon dioxide and of other pollutants, such as nitrogen oxides, sulfur dioxide – major drivers of the human-accelerated global climate change- must be monitored insitu. Our goal […]

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L2M – GradFinder

We are building GradFinder, an online platform that connects students with professors who are actively recruiting for thesis-based graduate programs. Many students struggle to find available positions, and professors are overwhelmed by unqualified inquiries. Our platform streamlines this process, improving access and efficiency on both sides. Through this project, we aim to refine our business […]

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Benchmarking fundamental components of quantum machine learning on full-stack photonic quantum computers

Architectures for quantum computing can only scale effectively with suitable benchmarking techniques. Benchmarking is essential for evaluating the performance of quantum computers, including their algorithms and applications. This principle extends to quantum machine learning techniques, where benchmarking basic quantum machine learning methods on full-stack photonic NISQ devices is crucial. A key challenge involves adapting quantum […]

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The Diagnostic Potential of Co-rotating Interaction Regions in Dense Hot-Star Winds

Wolf-Rayet (WR) stars exhibit strong, high-velocity winds with small-scale stochastic clumps and large-scale structures like Co-rotating Interaction Regions (CIRs). CIRs are spiral-shaped density enhancements, which propagate through the wind and induce variability in spectropolarimetric signals. WR6 (EZ CMa, WN4b) is a well-studied target with a stable 3.76-day periodicity in its wind variations. Recent observations, including […]

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Chelating bis(phosphinidenes) with cyclic alkyl(amino)carbene backbones: synthesis and coordination chemistry

This project focuses on developing new types of catalysts by designing and testing innovative molecules (ligands) that can better interact with metals and tune their properties. Catalysts are chemical species that help speed up chemical reactions, making them more efficient, selective, and sustainable. They are essential in many industries, from pharmaceuticals and petrochemicals to energy […]

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Design Principles of Biological Networks

This project aims to uncover the design principles of biological networks, such as blood vessels in the kidney and brain, by developing automated tools to analyze high-resolution 3D images of human embryo vasculature. Using advanced imaging techniques and deep learning, the research will create efficient methods to study how these networks efficiently transport nutrients and […]

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Density functional theory (DFT) assessment of new ligand designs for catalytic olefin polymerization – depolymerization

The upcoming research internship will explore hypothetical molecules derived from pyridine, which could be integrated in ligands for olefin polymerization and, potentially, depolymerization. Olefin polymerization is a catalytic process by which polyethylene and polypropylene are manufactured using catalysts incorporating unique ligand frameworks. This computational study aims to 1) determine the best ligand design for molecules […]

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Development of Climate and Infrastructure Forensic Analysis Systems: A BayesianPerspective

This project will upgrade the Climate and Infrastructure Forensic Analysis System (CIFAS), originally developed to characterize snow- and permafrost-related impacts to ground transportation and mine access roads in the Canadian North. My first objective is to enhance the analytical capacity of CIFAS by improving its ability to quantify uncertainties associated with empirical knowledge used to […]

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L2M-Materiax AI

This project will explore the market potential of a new technology that uses advanced artificial intelligence, powered by both classical and quantum methods, to help companies discover new materials faster and more efficiently. The intern will work closely with mentors and industry experts to identify which industries can benefit the most from this innovation and […]

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