Unravelling Proton Structure with Hyperoptimised Machine Learning

Proton structure

Large scale statistical data analysis in particle physics

Automated Parallel Calculation of Collaborative Statistical Models

JCER Optimized data handling Workflow technologies

PE Physical Sciences and Engineering PE2 Fundamental Constituents of Matter PE2_8 Gas and plasma physics

New tools for researchers in plasma, combustion and chemical reactor science

Passing XSAMS

Big data CERN Data Analysis High-energy physics High performance computing Large Hadron Collider Particle Physics

PE Physical Sciences and Engineering PE2 Fundamental Constituents of Matter PE2_2 Phenomenology of fundamental interactions PE2_3 Experimental particle physics with accelerators PE2_6 Nuclear, hadron and heavy ion physics

CEDAR is MCnet’s initiative to support sustainable, reusable software tools for collider phenomenology, including Rivet, YODA, and LHAPDF, enabling precision comparisons between theory and experiment.

CEDAR

fusion integrated tokamak simulation model coupling multiscale

Coupling physics and engineering codes for the experimental fusion reactor ITER

ITER Persistent Actors Framework

model coupling Multi-scale & multi model simulations

LS Life Sciences LS3 Cellular, Developmental and Regenerative Biology PE Physical Sciences and Engineering PE2 Fundamental Constituents of Matter

All projects

Proton structure

Automated Parallel Calculation of Collaborative Statistical Models

Passing XSAMS

CEDAR

ITER Persistent Actors Framework

Muscle4MUSCLE