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internal reports and manuscripts. Requirements: PhD in Physics, Materials Science, Computational Science/Engineering, Computer Science, or related. Solid knowledge of machine learning, including graph neural
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documentation. Contribution to applications to HPC centres (with a focus on EuroHPC machines) in order to secure the resources needed for architecture-dependent code development, optimised deployment and
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build using molecular dynamics, the MACE foundation models and density functional theory. Main Tasks and responsibilities: AI4LSQUANT aims to accelerate quantum modelling by learning fast, accurate
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of inflation and phase transitions in the early universe. We are developing new data analysis methods like the use of deep learning and the use of robust statistics. This work is naturally extended to studying
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documentation. Contribution to applications to HPC centres (with a focus on EuroHPC machines) in order to secure the resources needed for architecture-dependent code development, optimised deployment and
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on essentials. It’s like learning to ride a bicycle; once you grasp the fundamentals and the correct techniques, the rest becomes easy,” Liao says. A pilot programme called ‘Jieping Class‘ is underway at CMU