Awarded Projects

Digitalization is a longstanding goal of the EU, with varying degrees of progress among member states. Large language models are a promising catalyst for this process, but the current landscape presents significant challenges.

Multimessenger (MM) astrophysics promises to answer some of the most intriguing open questions in Physics, including the nature of gravity, the properties of nuclear matter, the origin of the heaviest elements.

This project proposes a new vision foundation model that rivals—and often surpasses—the performance of leading proprietary models such as DINOv2, CLIP, and SigLIPv2.

Understanding and simulating strongly correlated quantum systems is a central challenge in modern physics, with applications ranging from high-temperature superconductivity to quantum computing.

The properties of atoms, molecules and solids could all be computed reliably if we were able to solve the many-electron Schrödinger equation quickly and accurately enough.

The muon, a short-lived cousin of the electron, has provided a longstanding discrepancy between the standard model of particle physics and experimental measurements.

This project aims to explore and refine methods for the next-generation models for drug discovery

This project proposes to develop and evaluate a next-generation autoregressive visual generative model that combines the strengths of autoregressive transformers, large language models (LLMs), and diffusion models.

We request CPU and GPU hours of computational resources for calculating the equilibration of quark-gluon plasma (QGP) in high-energy heavy-ion collisions (HICs).