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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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executing research lines focused on the development of bio-inspired materials (coatings, nanoparticles, and membranes). Advanced and Polymeric Materials Development: Solid experience in the development
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executing research lines focused on the development of bio-inspired materials (coatings, nanoparticles, and membranes). Advanced and Polymeric Materials Development: Solid experience in the development
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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
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contracting some products (health insurance, childcare, training, among others.) Training activities: languages, mentoring programme, wellbeing programme. International environment Estimated Incorporation date
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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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advantages contracting some products (health insurance, childcare, training, among others.) Training activities: languages, mentoring programme, wellbeing programme. International environment Estimated
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Incorporation date: as soon as possible RIANA project: This project has received funding from the European Union's Horizon Europe research and innovation programme under grant agreement No. 101130652. How