Awarded Projects

This project develops cross-API agents that can complete real workflows spanning multiple software systems where actions must be coordinated end-to-end.

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).

This project investigates the learning of 3D world simulators directly from multi-view RGB videos.

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.

Atrial fibrillation (AF) represents a critical cardiovascular challenge, often complicated by significant interpatient variability and the limitations of current therapeutic interventions like Pulsed Field Ablation (PFA) and Radiofrequency Ablation (RFA).

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