11 coding-"https:"-"https:"-"https:"-"https:"-"https:"-"Dip"-"Dip" positions at ICN2 in Spain
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Research Engineer - Tools developer for LSQUANT platform (Theoretical and Computational Nanoscience)
the group's ongoing code development. Address and resolve security issues between the front end and back end. Create a user database for the Bespokematerial project. Develop a tool that allows users to select a
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for the long-term health of our code repositories and the versioning of models and data (Git, DVC, MLflow). Requirements: Education: Ph.D Degree in Computer Science, Engineering, Mathematics, Physics
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-corruption guide, supporting the curation of the ICN2 Ethics Code, coordinating and managing the signing of documentation, collaborating in obtaining data and preparing reports and providing the Generalitat de
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of strategic initiatives that embed artificial intelligence into ICN2's core activities. The platform promotes good coding practices and open‑source software principles, aiming to become a central and
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properties of high-entropy alloy (HEA) nanoparticles. The SIESTA code will be used to compute key descriptors such as formation energies, mixing enthalpies, adsorption energies, d-band centers, and work
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highly desirable. Knowledge on AI ML/DL coding applied to STEM / EELS data analysis automation is also needed. · Professional Experience: Previous research experience in an academic or industrial setting
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: MSc in Physics, Materials Science, Nanoscience, Computer Engineering, Data Science, Gaming Engineering or a related discipline. · Knowledge: Strong coding skills in Python and knowledge in materials
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. Creation of new functionalities: Design and implement new modules in both backend and frontend under the supervision of the senior team. Code quality (QA): Perform unit and integration testing to ensure
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widely used by the academic community (about one thousand citations per year), and has been a flagship code of the MaX European Centre of Excellence for exascale computing in Materials Science (www.max
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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