Supported projects

Supported projects

The EPICURE project supports a diverse range of initiatives, addressing support requests, e.g., from GPU and node optimization to code porting and performance benchmarking. Each project brings unique challenges and goals, and EPICURE provides the expertise and resources to help them succeed. On this page, you’ll find a selection of supported projects, showcasing EPICURE contribution.

Advancing RNA Therapeutics: Molecular Dynamics Insights into Lipid Nanoparticle Design and Optimization for Enhanced Delivery

The ModeLNP project received support for performance benchmarking, GPU optimisation, and software installation.

Supported projects

Machine Learning of Exchange Energy Density and Integration with Python-based Electronic Structure Codes

Seareport

Event Building at the Future Circular Collider: Machine Learning Based Particle Flow and Track Reconstruction

Advancing RNA Therapeutics: Molecular Dynamics Insights into Lipid Nanoparticle Design and Optimization for Enhanced Delivery

Investigation of novel epigenetic signals through combinatorial crosstalk between histone isoforms

Genie 2.0. and 3.0.: an optimized denoising diffusion probabilistic model for protein design

RAHMAN

Scaling Deep Neural Networks for Public Safety: Fire, Flood etc. with HPC

Enhancing AI training efficiency and scalability to train EU institutional LLMs for the public sector

Large-Eddy Simulations of Supersonic Air Intakes

AtmoRep: Large Scale Representation Learning of Atmospheric Dynamics

Supported projects

Supported projects

Machine Learning of Exchange Energy Density and Integration with Python-based Electronic Structure Codes

Seareport

Event Building at the Future Circular Collider: Machine Learning Based Particle Flow and Track Reconstruction

Advancing RNA Therapeutics: Molecular Dynamics Insights into Lipid Nanoparticle Design and Optimization for Enhanced Delivery

Investigation of novel epigenetic signals through combinatorial crosstalk between histone isoforms

Genie 2.0. and 3.0.: an optimized denoising diffusion probabilistic model for protein design

RAHMAN

Scaling Deep Neural Networks for Public Safety: Fire, Flood etc. with HPC

Enhancing AI training efficiency and scalability to train EU institutional LLMs for the public sector

Large-Eddy Simulations of Supersonic Air Intakes

AtmoRep: Large Scale Representation Learning of Atmospheric Dynamics

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