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theoretical and practical experience with machine learning methods, especially for training of machine learning potentials - development and utilization of ab initio electronic-structure methodology - previous
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on both fundamental magnetic interactions and applications for efficient energy conversion. We use element-specific methods such as X-ray absorption spectroscopy at synchrotron radiation sources and
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characterization of interface deformation mechanisms, including advanced SEM and TEM methods Finite Element Modeling to design and optimize micromechanical testing geometries Timely dissemination of research
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computer aided methods. Qualifications and Experience • Outstanding academic degree in materials science, metallurgy, metal physics or similar degree • Excellent doctorate with focus on computational
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approaches to address current questions with relevance to society (e.g., sustainability, inequality, corporate governance). We work with both qualitative and quantitative empirical methods. Our teaching is
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Centre, the Neutron-SimLab or various physicochemical characterization methods and workshops. The opportunity to help shape a new department. Access to the infrastructure of the Institute
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Max Planck Institute for Evolutionary Biology, Plön | Plon, Schleswig Holstein | Germany | 14 days ago
the intertidal midge Clunio marinus (Diptera) as a model organism and apply methods ranging from molecular biology and evolutionary genomics to behavioral experiments and ecological field work. We are looking
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of precursors in gram scale batches for thin film deposition of functional nanostructured materials Characterizing precursors via SC-XRD, NMR, FTIR, Thermal Analysis (TG-DTA) and other analytical methods Your
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, responsible and independent work Friendly and co-operative working atmosphere in a small team Thorough familiarization with new working methods and equipment State-of-the-art working conditions in a future
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molecular/condensed matter physics) and the developments on new tools in perturbation theory and in computational methods (gradient flow), including quantum computing. We look for ambitious candidates with a