UNIVERSITE PARIS SCIENCES ET LETTRES

Their core work

PSL University is a prestigious Paris-based research university that applies artificial intelligence and data science methods across multiple scientific disciplines — from precision medicine to physics, chemistry, and cognitive sciences. Their H2020 work focuses on training the next generation of researchers at the intersection of AI and fundamental sciences, bridging quantitative methods with domain expertise. They also participate in building European university alliances to promote open science and shared research strategies across institutions.

What they specialise in

How they've shifted over time

PSL's H2020 trajectory shows a clear broadening of scope. Their earliest involvement (2019) targeted a specific application — machine learning for precision medicine. By 2020-2021, they expanded to position AI as a cross-disciplinary tool spanning physics, biology, chemistry, economics, and cognitive sciences, while also joining a European university alliance focused on open science and citizen engagement.

PSL is moving from domain-specific ML applications toward becoming a broad interdisciplinary AI training hub, suggesting future collaborations will emphasize AI methods applied to diverse scientific fields.

How they like to work

PSL takes varied roles — coordinator, partner, and third party — showing flexibility in how they engage with consortia. With 25 unique partners across 13 countries from just 3 projects, they operate in large, internationally diverse networks rather than tight recurring clusters. This suggests they are open to new partnerships and comfortable working with unfamiliar teams.

Despite only 3 projects, PSL has built connections with 25 distinct partners across 13 countries, reflecting the large consortia typical of MSCA training networks. Their reach spans broadly across Europe with no single dominant partner country.

What sets them apart

PSL brings together excellence across an unusually wide disciplinary range — engineering, physics, biology, chemistry, economics, and cognitive sciences — all connected by a common thread of AI and quantitative methods. For consortium builders, this means a single partner that can contribute both methodological AI expertise and deep domain knowledge in multiple scientific fields. Their MSCA coordination experience also makes them a strong candidate for training and doctoral network proposals.

Highlights from their portfolio

• AI4theSciences
  PSL's largest project (€2.1M) and coordinator role — an MSCA-COFUND program training doctoral researchers in AI applied across physics, biology, chemistry, economics, and cognitive sciences.
• MLFPM2018
  An MSCA-ITN network applying machine learning to precision medicine, connecting PSL to the growing health-AI research community across Europe.