AI for catalyst discovery

In this project, we will develop innovative AI tools to speed up the process of catalyst discovery, in particular in the domain of renewable energy. Specific catalysts are essential to applications such as the efficient synthesis of solar fuels and fertilizer. However, many known catalysts are suboptimal in their efficacy or require scarce elements. Currently, […]

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Process intensification for production of rVSV

To prevent diseases such as coronavirus disease 2019 (COVID-19) and Ebola virus disease vaccines are the most effective tool. For this, the promising viral vector recombinant vesicular stomatitis virus (rVSV) is applied as production platform. Using suspension HEK293 cells, rVSV-based vectors are currently only produced in batch mode. However, the establishment of perfusion cultivations at […]

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Étude des effets cognitifs et physiologiques de la prise de retraite

L’augmentation de l’espérance de vie et le recul de l’âge moyen de départ à la retraite font que le temps passé à la retraite est plus important qu’auparavant. La prise de retraite pourrait accélérer le déclin cognitif associé au vieillissement. Or, un mode de vie caractérisé par une activité physique élevée et un faible niveau […]

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Genre et migration : portraits de l’émergence des renégociations militantes en temps de crise sanitaire au Chiapas

J’explore dans ma recherche les différentes formes de solidarités et soins dans la ville de San Cristobal de las Casas ( Mexique). L’idée est de produire une analyse des modalités et des réseaux d’appui entre femmes, en incluant des espaces d’hébergement, (refuges ou espaces d’accueil) dans la région sud du Mexique. Cette région est une […]

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Caractérisation du rôle de la famille des prokinéticines dans le contrôle de la chorioamniotite et dans les conséquences neurodéveloppementales néonatales.

La chorioamniotite, infection ascendante de la grossesse est une cause majeure de prématurité et de paralysie cérébrale chez les enfants prématurés. Le laboratoire du Pr Sébire (Research Institute of McGill University Health Center, Montréal) a mis au point un modèle de rates gestantes présentant une chorioamniotite induite par du streptocoque du groupe B. Au cours […]

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Caractérisation non destructive des enrobés bitumineux

Les enrobés bitumineux sont majoritairement utilisés pour revêtir les structures de chaussée. La caractérisation de leur comportement thermomécanique est donc essentielle pour comprendre leur fonctionnement sous charge et dimensionner correctement les structures neuves ou qui doivent être réhabilitées. À l’heure actuelle, la majorité des essais qui permettent de caractériser ces matériaux en laboratoire nécessite des […]

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Novel rhamnolipids for a sustainable bioeconomy

Today’s society faces several challenges in implementing and enforcing environmental protection for future generations. In this respect, supplementation of petro-based chemicals by bio-based ones is of special importance to reduce the consumption of crude oil. Among such measures, chemical surfactants can be replaced by biosurfactants, e.g. rhamnolipids which are produced via fermentation from renewable resources […]

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Carbon coating to improve Titanium and Aluminum powder properties for LPBF application

Aluminum and titanium components fabricated via laser powder bed fusion (LPBF) process have gained industry interest, especially for automotive and aerospace applications, due to their enhanced lightweight and mechanical properties. For a higher part quality and surface resolution, the use of fine powders is desired for the LPBF process. However, the poor flowability of fine […]

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Attack Detection for 5G Networks using AI/ML

The roadmap for 5G networks is already taking shape due to several industrial and academic research efforts. 5G networks are expected to support more diversified services, which should create exciting business opportunities in many vertical sectors. Achieving this requires improving the technologies behind the evolution of 5G and leveraging machine learning (ML)/artificial intelligence (AI) techniques […]

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Making AI Ready for Safety-Critical Applications

This project is a collaborative endeavor of researchers (6 supervisors, 3 PhD students and one postdoctoral fellow) which will be either members or visitors of the incoming “International Laboratory on Learning Systems” (ILLS) of the CNRS (starting in early 2022) with Université Paris-Saclay, McGill University and École de technologie supérieure (ETS). We will develop rigorous […]

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AI based technology adoption in circular economics

This project is a cross-disciplinary study of econometrics and machine learning (ML) models applied to the decision making modelling in industry. The problematic arises from the lack of tools supporting the transition to circular economics model and the need to identify the key factors to influence this transition. The project aims to explore the key […]

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