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of Group/Project: We are building an optimisation-driven framework that makes AI models reliably operate advanced scientific software (e.g., DFT, Wannierisation, and quantum-transport codes) and (ii) uses
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materials data bases together with novel AI tools. Requirements: Education: · Undergraduate in Physics, Chemistry, Materials Science, or related disciplines. · PhD in Physics, Materials Science, Chemistry
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benchmarking. Contribution to SIESTA training events. Contribution to other activities in the group. Requirements: PhD in Physics, Materials Science, Chemistry, Computer Science, or related disciplines
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institution and they are allocated through recurrent internal calls). Preparation of scientific reports, journal articles and software documentation. Requirements: PhD in Physics, Materials Science, Chemistry