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Awarded Projects (425)
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The atom-scale design of surfaces holds enormous potential for applications such as catalysis or superlubricating interfaces: Approximately 24% of the global energy consumption is lost to friction, while the chemical industry consumes around 29% of the energy in the manufacturing sector.
The origin of multiple stellar populations (MPs) in globular clusters (GCs) is one of the most puzzling issues of stellar astrophysics. Many attempts have been done both from observational and theoretical studies to unveil the enigma of their formation but, so far, a clear picture is still lacking.
Within the framework of the European Innovation Council project MOJITO, this project aims to elucidate the atomistic mechanisms governing CaCO3 calcination through large-scale molecular dynamics (MD) simulations based on machine learning potentials (MLPs).
The well established theory of strong interactions (Quantum Chromodynamics) has yielded a huge amount of understanding how the nucleon and other hadrons are built from quarks and gluons, the fundamental degrees of freedom in QCD.
Radiotherapy (RT) is one of the most frequently used methods for cancer treatment (above 50% of patients will receive RT). Despite remarkable advancements, the normal tissues tolerances continue being the main limitation in RT.
The design of synthetic/artificial molecular systems to finely control chemical reactions is a key challenge, with countless technological applications.
This project aims to develop a Large Language Model (LLM) with a strong focus on Italian and other European languages, counterbalancing the current dominance of English in AI systems. Existing open models that comply with the European Union’s Artificial Intelligence Act (AI Act) are very few.
The objective of this project is to develop a lidar foundation model capable of promptable 3D segmentation and detection and exhibiting strong generalisation across diverse autonomous driving datasets.
The proposed project aims to advance multilingual Natural Language Processing (NLP).
Hormone-sensitive prostate cancers eventually stop responding to hormone therapy. A new treatment regimen may or may not work. That is why it is important to apply optimal therapy against hormone-sensitive prostate cancer at its earliest stage.