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materials (sputtering, PLD, wet-chemistry approaches), lithography (optical, e-beam), magnetometry equipment (VSM, MOKE), electrochemistry (galvanostats), ferroelectric characterization of materials
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postdoc to support advanced characterization efforts within the framework of the IMPRESS project, a European initiative involving international partners. This project aims to tackle the global challenge
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build using molecular dynamics, the MACE foundation models and density functional theory. Main Tasks and responsibilities: AI4LSQUANT aims to accelerate quantum modelling by learning fast, accurate
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AI4Science project, specifically focusing on the intersection of advanced machine learning and sustainable catalysis discovery. The primary incentive of this Postdoctoral Fellowship is the chance to contribute
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valued. · Knowledge of chemical reactions and how to model them through computer simulations is highly valued. · Knowledge of classical molecular dynamics, including Machine Learning Interatomic Potentials
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the scientific literature relating to (and around) the project · To undertake any necessary training · To learn and develop new research skills outside own discipline · Any other reasonable duties commensurate