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computational methods to investigate quantum, optical, thermal and spin-dependent transport in complex materials. A central expertise of the group is the LSQUANT methodology, a suite of linear-scaling, real-space
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Computational Nanoscience group at ICN2 develops theory, models and large-scale simulation tools for quantum transport, spin dynamics and emergent computing in low-dimensional materials, in close contact with
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with large-scale research infrastructures, such as synchrotrons, is an advantage. Personal Competences: Strong problem-solving skills and the ability to work independently as well as part of a
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for energy materials or catalysis, skills on in-situ TEM will be a plus. Experience collaborating in international, multidisciplinary projects is a plus. Hands-on experience working with large-scale research
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in altermagnets to encode and process information. The project involves close collaboration with experimental and theoretical partners, including large-scale synchrotron facilities. The work will be
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beyond conventional binary "bits" toward multi-level and analog memory systems that enable richer information encoding. A major thrust of the group is the development of in-memory and physical computing