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to) SIESTA (www.siesta-project.org) and its TranSIESTA functionality. SIESTA is a multipurpose first-principles method and program, based on Density Functional Theory, which can be used to describe the atomic
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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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compensation plan: tax advantages contracting some products (health insurance, childcare, training, among others.) Training activities: languages, mentoring programme, wellbeing programme. International
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to) SIESTA (www.siesta-project.org) and its TranSIESTA functionality. SIESTA is a multi-purpose first-principles method and program, based on Density Functional Theory, which can be used to describe the atomic
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/Project: The NanoElectrocatalysis and Sustainable Chemistry Group combines electrochemistry, materials engineering and in situ characterisation at the atomic scale to elucidate design principles
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(health insurance, childcare, training, among others.) Training activities: languages, mentoring programme, wellbeing programme. International environment Estimated Incorporation date: as soon as possible
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, training, among others.) Training activities: languages, mentoring programme, wellbeing programme. International environment Estimated Incorporation date: January 2026 How to apply: All applications must be
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products (health insurance, childcare, training, among others.) Training activities: languages, mentoring programme, wellbeing programme. International environment Estimated Incorporation date: November 2025