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This project will deliver open research artifacts (code, models, and evaluation protocols) to support efficient, trustworthy, and sustainable foundation-model research in Europe.
This project introduces a paradigm shift in binary code analysis by transferring the concept of semantic embeddings from natural language processing to compiled software.
Colloidal Quantum Dots (QDs) are nano-sized crystallites notable for their exceptional semiconductive properties, which were recently acknowledged with the Nobel Prize in Chemistry.
This project focuses on the design of lipid nanoparticles (LNPs) for efficient RNA-based therapeutics delivery, addressing critical challenges in the field.
Radiotherapy (RT) is one of the most frequently used methods for cancer treatment (above 50% of patients will receive RT).
This project is concerned with the general problem of nano-pollutant removal. The final objective is to provide a reliable framework for the study of aggregation and removal of suspended solids by means of Nanobubbles.
This proposal develops an AI-driven, multi-pollutant model for operational regional air-quality forecasting over Europe, implemented within ECMWF’s Anemoi framework.
Contact line phenomena entail multi-physics processes that operate at disparate scales, often posing formidable large-scale computing challenges.
QuantaPep is an end-to-end AI-driven peptide discovery platform developed by Rejuvenage Kft., targeting longevity-relevant pathways including sirtuins, AMPK, and mTOR.
Probabilistic (p-bit) and oscillator-based computing are leading routes to energy-efficient AI and optimisation hardware, both built from nanomagnetic devices whose figures of merit emerge only from finite-temperature micromagnetic dynamics. This project designs such hardware.