Awarded Projects

This project focuses on investigating the fundamental aspects of hydrogen turbulent combustion.

This proposal will contribute to building two European Storm-Resolving Earth System Models (SR-ESMs), applying them to study the Earth system and answering important open questions about how its climate will change over the next decades.

The primary challenge is to obtain an accurate impact rate for the last 1 Gyr of evolution due to substantial particle loss. We are further challenged by the duration of the simulations versus that of the project.

Climate change and pollution urge the aeronautical sector to reduce its environmental footprint.

This project addresses some limitations in he primary workhorses of quantum simulations by developing thermaMLS2, a real-space machine-learned correlation model that builds on our recent work on local-energy learning and perturbation-theory-based density functionals.

Machine learning plays a pivotal role in extending the reach of quantum-chemistry methods for simulating molecules and materials.

This project proposes novel methods leveraging multi-modality and foundation models to correct SpT data for unwanted sources of variation while preserving the biological signal and at adapting downstream analyses including adapting differential gene expression analysis (DGE) to newly corrected data.

Olfactory receptors (ORs) are the largest subfamily of G-protein-coupled receptors (GPCRs). ORs evolved to interact with the outside world by detecting volatile molecules called odorants.

The project aims to revolutionise insurance claims processing by developing Insoore GenAI, a technological platform leveraging advanced GenAI models to automate damage assessment, enhance customer experience, and prevent fraud.