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This project addresses critical gaps in regional data-driven weather modeling by exploring ML techniques capable of high-resolution forecasting for complex Alpine terrain, with implications for advancing both scientific understanding and practical applications in similar regions worldwide.

The project focuses on creating advanced generative modelling pipelines to accelerate research, diagnosis, and understanding of Neglected Tropical Diseases (NTDs) affecting the skin, a domain where data scarcity, geographical inequity, and clinical variability remain major barriers to innovation.

A molecular level understanding of skin permeation may rationalize and streamline product development and improve quality and control, of transdermal and topical drug delivery systems.

Optogenetics uses light to control the activity of specific cells, and it has revolutionised neuroscience research. Genetically modified cells express light-sensitive proteins called opsins, which are activated when exposed to light of a specific wavelength.

his project aims to to develop the next generation of an open-source model for Slovene called GaMS. The model will be the basis for further adaptations to specific application needs and will also be available for wider academic and industrial use.

This is project meant to support the Smart-TURB ERC AdG (2021-2026) on Machine Learning applications to Eulerian and Lagrangian Turbulence.

This is a key contribution of Lattice Field Theory to Particle Physics at the precision frontier.

The project proposes a high-statistics computation of lattice correlation functions starting from isospin-symmetric QCD and including the leading isospin-breaking effects.

SoftQuantus aims to scale its flagship model, SynapseX LLM, leveraging the LUMI-G EuroHPC JU infrastructure to advance sustainable, quantum-enhanced generative AI for industrial and financial domains.

The simulation results are expected to drive improvements of reduced-order models and establish a reproducible methodology for BBN predictions in a realistic strongly compressible context.