Awarded Projects

Fossil fuels energy production is steeply increasing with correspondingly increasing atmospheric carbon dioxide (CO2) emissions.

This project capitalises on previous AI research utilising LLMs to analyse vast and diverse phage and bacterial genomic datasets to train the first generative model able to adapt phage genomes to new hosts.

The project proposes to perform the first global simulations of plasma fluid turbulence in the W7-AS stellarator. The simulations will be performed with GBS, a three-dimensional turbulence code that solves the drift- reduced Braginskii equations in a toroidal domain and with first-principles sheath

Tremendous progress has been made in magnetic confinement fusion research over the past decades, culminating in the recent world record energy output recorded at JET. However, the challenge of achieving a self-sustaining plasma remains.

We propose to conduct global MHD simulations of the whole Solar convection zone. This first-of-a-kind simulation will connect internal dynamo simulations to the surface of the Sun on a global scale.

This project aims at studying the turbulent flow of two immiscible fluid layers of different properties, between two parallel walls of idealized rectangular channel geometry.

The understanding and tuning of the electronic properties of graphene on metals, possibly encompassing magnetism, is crucial towards the inclusion of graphene into devices, and graphene-based electronics on a large industrial scale.

This project addresses critical shortcomings in large language models (LLMs), particularly hallucinations (factually incorrect yet plausible-sounding outputs), embedded biases, and the inclusion of copyrighted material in training data.

Turbulent flows laden with drops are ubiquitous in nature and in our everyday life. These flows play a key-role in various applications, from geophysical phenomena to food and industrial processes.