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optimiser that accelerates both workflow efficiency and materials discovery. Main Tasks and responsibilities: AI4LSQUANT aims to accelerate quantum modelling by learning fast, accurate surrogates
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familiarity with at least one of: DFT workflows, Wannier/TB model building, or quantum-transport simulations; willingness to become hands-on across the stack. Comfortable with Linux/HPC, job schedulers, and
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environmental conditions relevant to catalysis and PEC operation. · Work closely with national and international collaborators by offering hands-on support and guidance for in-situ TEM experiments. · Train
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of these novel materials for their application in tissue regeneration, infection diseases and cancer. Other applications will be explored as for example in environmental remediation. The candidate will primarily
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of these novel materials for their application in tissue regeneration, infection diseases and cancer. Other applications will be explored as for example in environmental remediation. The candidate will primarily
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spectroscopy (EDS) and electron energy loss spectroscopy (EELS). The research will involve state-of-the-art nanomaterials for energy and environmental applications as well as nanomaterials for quantum