Projets novateurs réalisés

Predictive Modelling and Functional Validation Of Long non-coding RNAs In The Heart

This research proposal aims to employ cutting-edge machine-learning tools to classify the a group of RNA molecules in heart cells and thereby unravel their function

La politique d’influence des entités supranationales : corrélation et délégation des capacités d’attraction des États membres au sein de l’Union européenne

Le projet de recherche se propose d’analyser les éléments qui constituent l’attractivité de l’Union européenne à l’international et surtout dans les États post-soviétiques que sont l’Ukraine, la Moldavie et la Géorgie. Il permettra de comprendre quels sont les acteurs qui influencent le plus l’Union européenne et la façonnent au quotidien. Il permettra d’évaluer les limites qu’ils ont sur le plan national et qu’ils peuvent compenser en travaillant en équipe avec les autres États membres. Cet échange permettra de lancer une réflexion sur les actions à entreprendre pour renforcer l’attractivité de l’Union et de savoir sur quels points celle-ci ne peut pas se substituer aux pays qui la composent.

LegiSimple – Enhancing Legal Research Efficiency Through AI-Powered Case Law Search

LegiSimple is an innovative project designed to simplify the legal process for lawyers, notaries, and paralegals in Quebec and Canada. The project leverages advanced AI to drastically reduce the time required to analyze, interpret, review, find jurisprudence, and refer to case law. This technology enables legal professionals to focus more on strategic aspects of their business rather than being bogged down by time-consuming tasks.

The primary goal of the LegiSimple project is to enhance the efficiency and productivity of legal professionals. By streamlining legal processes, LegiSimple aims to ensure that lawyers, notaries, and paralegals can perform their duties more effectively, ultimately leading to increased satisfaction and perceived value among users.

Interns working on the LegiSimple project will be responsible for helping to manage the code base, ensuring that all systems run smoothly. They will also contribute ideas to improve the product and the company, helping to drive innovation and efficiency within NeoGPT Technologies.

LegiSimple is primarily a process innovation project. It focuses on improving the efficiency and effectiveness of legal processes through the use of advanced AI technology. The project will employ a combination of agile development methodologies and user-centered design techniques. This includes regular iterations and feedback loops with end users to ensure that the product meets their needs and expectations. Data analysis and machine learning techniques will be extensively used to refine and enhance the AI models that power LegiSimple.

Advanced electrochemical analysis tools and methodologies

Pulsenics is a leading technology company specializing in advanced electrochemical analysis tools and methodologies. Their primary focus is on developing cutting-edge solutions for monitoring and optimizing electrochemical systems, including batteries, electrolyzers, and fuel cells. The company’s flagship technology, Electrochemical Impedance Spectroscopy (EIS), is utilized to assess the performance, health, and efficiency of various electrochemical devices without causing damage. Pulsenics aims to enhance the reliability and longevity of these systems by providing real-time data and insights into their internal processes.

Pulsenics is facing the challenge of improving the accuracy and reliability of battery stack performance evaluations. Traditional EIS methods, while effective, are time-consuming and can be limited by hardware constraints, such as power limitations and signal distortions. There is a need to optimize EIS protocols to provide faster, more detailed, and more reliable data, which will help in the early detection of issues and the enhancement of battery performance. The priority is to develop an advanced EIS protocol that leverages multisine signals and integrates machine learning techniques to enhance the resolution and reliability of battery performance data. This improved protocol should address hardware constraints and be validated through both simulation and real-world testing. This project will significantly advance Pulsenics’ capabilities

Enhancing Knowledge Self-Awareness in Large Language Models through Self-Explanation and Self-Reflection

Large language models (LLMs) are becoming ubiquitous given their ability to excel at many tasks. However, there has yet to emerge a comprehensive understanding of their internal mechanisms, in particular with regards to how LLMs use the knowledge it possesses. Previous works have suggested that despite LLMs possessing knowledge, they can often be incapable of using it directly. However, additional works have also proposed the use of self-explanations as a way to induce LLMs to rationalize and explain their behaviour, enabling for the analysis of LLMs even without explicit access or understanding of their internal dynamics. For this end, self-explanations also provide an avenue to better understand whether LLMs understand the scope of their knowledge and if they can use this information to achieve factually correct responses, even if such information is not directly known. Using LLMs within self-reflective loops, we can uncover how LLMs understand the information it has been trained on, how it accesses this information for downstream purposes as well as whether or not it can understand when necessary information is missing, providing an improved understanding of LLMs and better utilizing them in more reliable ways in the future.

Optimizing Anaerobic Digestion of Food Waste

In Canada every year, approximately 20% of the food produced becomes waste and food waste is Canada’s largest residual municipal solid waste category. Despite diversion strategies like composting, 28% of residential and 25% of industrial, commercial, and institutional solid waste is comprised of food waste and landfilled or incinerated. Food waste can be converted to valuable resources, for example anaerobic digestion relies on the activity of diverse groups of microbes to degrade food waste and convert it to biogas, which can be used in a similar manner to natural gas, and fertilizers useful for crop production. Although a useful technology, improvements to the anaerobic digestion process is possible by gaining a greater understanding of the relationship between various food waste feedstocks and the metabolic activity of different microbial groups. This project will analyze production of markers of microbial metabolism, lactic acid and volatile fatty acids, in response to different types of food waste. A greater understanding of the complex biological and chemical reactions occurring in anerobic digesters will lead to greater capacity to treat food waste and to increase the value of the biogas and fertilizer products via increased yields.

Machine Learning and Software engineer interns working with public and private sector organizations to develop and commercialize AI-powered solutions

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Double diplôme de doctorat : Effets d’entraînements d’exercices aérobie, avec ou sans gravité artificielle, sur la régulation de la prise alimentaire et de la balance énergétique pendant un analogue de microgravité de 60 jours chez l’homme sain

Lors des missions spatiales, les astronautes perdent souvent du muscle en raison de la microgravité, ce qui pourrait être aggravé par une balance énergétique négative, c’est-à-dire consommer moins de calories que celles dépensées. Pour les prochaines missions, les agences spatiales considèrent la gestion de cette balance comme essentielle. Cependant, peu d’études ont exploré comment l’exercice, un élément important de la dépense énergétique, influence l’apport énergétique en microgravité. Il se pourrait que l’exercice intense recommandé pour protéger la santé des astronautes entraîne aussi une perte de poids involontaire et non soutenable à long terme.

Notre étude vise à vérifier cette hypothèse en simulant la microgravité pendant 60 jours à l’aide du modèle physiologique le plus complet en ce sens ; l’alitement prolongé avec la tête légèrement inclinée. Ce modèle, couramment utilisé en recherche spatiale, permet de reproduire les conditions vécues par les astronautes. Nous évaluerons l’effet d’exercices aérobie et de gravité artificielle sur la régulation de l’énergie et la prise alimentaire. Ce projet aidera à mieux ajuster les prescriptions d’exercice et l’alimentation pour les futures missions spatiales et pour les personnes alitées sur Terre.

La dimension spirituelle de la naissance. Dialogue des épistémologies Nord et Sud pour une anthropologie transversale de la naissance

L’introduction des chirurgiens dans les couches des grandes familles à partir du XVIIe siècle qui peu à peu dressait une frontière entre la naissance et la nature a permis à une autre forme d’anthropologie de la naissance d’émerger en Occident : les pratiques obstétricales biomédicalisées. La science et la technologie remplacent les valeurs spirituelles qui définissaient l’être humain. Ces avancées deviennent des normes universelles, même dans les sociétés dites traditionnelles. Les discours sur la quête du sens et ce besoin spirituel face à l’adversité, la maladie, etc., montrent qu’il y a l’absence de cohésion sociale et de voies qui puissent aider les humains à se connecter avec les autres, la nature, etc. Cette étude mettra en dialogue Tillich et le vodou, qui postulent que l’être humain est pluralité afin de poser la question de naissance dans une compréhension plus large, selon les rites de passage. De la conception à la vie et de la vie à la mort, où à chaque période de l’existence humaine, une nouvelle naissance se produit. Les avantages escomptés sont la mise en œuvre d’une épistémologie de l’Autre, c’est-à-dire une vision du monde intra-relationnelle face aux cloisonnements culturel et religieux, qui serviront aux pratiques obstétricales techno-médicalisées.

Optical detection of free carriers in 2D materials

This project will focus on the optical detection of free carriers in 2D materials. The insights gained will enable the extraction of carrier numbers from the absorption and emission spectra of 2D crystals subjected to high magnetic fields. Understanding the optical responses of low-dimensional, many-body systems is crucial for advancing future optoelectronic devices in quantum technologies. Developing a theoretical framework for the optical properties of correlated electrons in 2D crystals will clarify the nature of the many-electron ground state in systems such as transition metal dichalcogenides, bilayer graphene-based field-effect transistors, and gated quantum dots. This progress opens pathways for controlling light-matter interactions through carrier density, exploring quantum sensing of single photons via trions in gated quantum dots, and designing novel optoelectronic devices for quantum computing applications.

Dreamcatcher Informatics: a Web-based and Mobile Information System to Support Land Management, Consultation, and the Preservation of History, Culture and Traditional Ecological Knowledge

The role of this internship is to assist in reaching the SSHRC goal for the Dreamcatcher system of capturing cultural data, traditional ecological knowledge, and traditional land use in order to create as full of a historical, cultural, and economic record as is possible as well as strong land use management/consultation, water management, asset management, and public health systems. This information will inform cultural research, treaty negotiations, and community development. This goal will be reached by the intern: 1) transcribing and upload source material from the various archives (Peter Jones, Library and Archives Canada, Mississaugas of the New Credit First Nation) to Dreamcatcher, 2) using this source material, researching family life of the Mississaugas of the New Credit First Nation and the role of Indian Agents in their lives, and 3) disseminate the collected data through narratives written for inclusion in the Dreamcatcher system and through co-authoring of articles.

High throughput tissue distribution study of polymer-lipid nanoparticle formulations using DNA barcode technologyy

Our project aims to develop polymer-lipid hybrid nanoparticles (pLNPs) to enhance gene delivery to cells
throughout the body, addressing two major challenges: ineffective release of genetic material inside cells
and limited targeting of non-liver tissues. By incorporating a pH-sensitive material, our pLNPs are designed
to improve the release of their genetic cargo within cells while expanding their reach beyond the liver. This
innovation has the potential to significantly advance gene therapy, which involves delivering therapeutic
genes for various diseases. We will employ advanced techniques to create and test a diverse range of
pLNP formulations in living organisms, establishing a library of unique delivery systems. Ultimately, this will
enable us to select the most effective formulations for precise and efficient gene delivery tailored to specific
diseases.