This project aims to provide a solution to a critical problem in existing superconducting quantum processors by developing methods to create long-range interactions. Superconducting qubits are one of the most promising platforms for building quantum computers. Currently, quantum processors based on this technology offer the largest quantum memories, but do not benchmark well in terms […]

Avec le développement en parallèle de technologies de traitement automatique des langues de plus en plus performantes, de théories linguistiques de plus en plus précises et de banque de données de plus en plus riches, il est maintenant plus facile de comparer les langues et d’identifier leurs points communs et leurs divergences. Un défi pour […]

This project will apply causal discovery methods to two model-generated datasets. One is a dataset describing the transport of emerging contaminant metformin in the groundwater; the other is a card fraud transaction dataset. The method will examine the dataset’s underlying structure (data skeleton). Multiple new methods will be evaluated and tested on the datasets. The […]

The Data Science/Analytics team at Voices is looking for a Data Analyst Intern to join the team and support analytics initiatives from developing Tableau reports to provide an in-depth/holistic understand of the platform, leveraging our datasets to provide insights/recommendations to decision makers, and producing predictive models on KPIs (i.e. retention, hire rate) to surface prescriptions/improvement […]

Since 2003, Humanware develops a GPS-based dedicated device that helps blind people to orient themselves and guides them to their destination. In this project, we want to enhance the user experience by providing a better understanding of the environment and interacting with the device in a more natural way. This project specifically addresses how the […]

We leverage a new, original dataset containing all recorded political donations made in all 14 Canadian jurisdictions since 1993 to map patterns in political donations and to measure the effects of donations laws. We ask: which types of individuals are more likely to make donations? What can the recipients and the timing of donations tell […]

This project involves interning for the Cansbridge Fellowship in Canada. The primary focus of the work-term will be to study the methods that such business used to scale from inception to present day in Asia virtually while interning for the Cansbridge fellowship. The methods of growth will focus on three aspects: (i) access to early […]

This project builds on ongoing research within the project ((Border-Crossing Books) which focused on the ways in which book cultures explicitly intersect with national identities in the twenty-first century. This project began by examining the circulation and reception of national literatures in the US, UK, and Australia from 2000–2020; this project will also be expanded […]

A nuclear reactor to a nuclear power plant is the same as the heart to a living human. Safe operation of the plant is directly related to the health of the reactor. Just as human heart where blood circulates through to deliver oxygen to the other parts of the body, coolant passes through the reactor […]

Marine emergency incidents pose major environmental risks that are detrimental to the ocean ecosystem and present significant dangers to both people and property. Current response options are very limited and the existing tools to deal with nearshore environmental spills are neither timely nor efficient. SHIFT Environmental is developing innovative solutions as part of a Coastal […]

Attention is a key process to many daily tasks but it is characterized by limited resources. In many high-stake domains, operators must perform complex tasks for long durations, which deplete attentional resources and promote error making. Yet, previous studies have shown that exposure to nature stimuli can help recovering those resources. The current project aims […]

In this project, the intern will work with an expert team from the company Zapata, to compare the performances of machine learning models on classical computers and on quantum models in terms of generalization to unseen data