Awarded Projects

The main goal of the heavy ion program of many accelerator facilities (LHC, RHIC and the upcoming CBM/FAIR) is to create new phases of matter and explore their properties under extreme conditions.

As Big Tech acquires the advanced hardware components necessary to build private, special-purpose computing clusters, this project advocates for a new approach to publicly supported computing power in general, and on LLM pre-training in particular, through cross-Facility Federated Learning (xFFL).

The resolution revolution has increasingly enabled single-particle cryo-EM reconstructions of previously inaccessible systems, including large membrane protein complexes that constitute a disproportionate share of drug targets.

RNA molecules span a great variety of biological functions, from genetic information storage to catalysis. This is possible thanks to the highly heterogeneous conformational ensembles that these molecules can adopt.

The goal of this project is to reach a new frontier in precision radiology by developing foundation models for 3D medical imaging, trained with self-supervised learning (SSL) techniques at an unprecedented scale.

This project will use the computational resources of EuroHPC to perform a systematic study and scale up experiments to build LLMs for four European languages with few resources.

This project concerns the pre-training of a foundational multilingual large language model with billion of parameters that excels at Danish.

DataROC generates potential therapeutic targets for biomedical scenarios of interest, alongside a proposed mechanism of action, origin, and disease impact for each target.

This project aims to go beyond designs based on human intuition and discover a new class of tunable gravitational wave detectors with enhanced sensitivity.