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: Atomistic & Molecular Modelling for Catalysis Group Where to apply Website https://cicenergigune.com/en/employment-opportunities/111296823 Requirements Research FieldChemistryEducation LevelPhD or equivalent
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of dissertation topics: Development of Machine Learning Frameworks for Reactive Atomistic Materials Modeling (DSP II) Profile of the graduate This Ph.D. program is an interdisciplinary study combining physical
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) to organize simulation outputs for analysis, benchmarking, and reproducibility. Document workflows and contribute to publications and dissemination activities within the project. Where to apply Website https
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the Forschungsverbund Berlin (https://www.fv-berlin.de/ ) and the Leibniz Association www.leibniz-gemeinschaft.de . You can find more details on the institute webpage: www.ikz-berlin.de . The Section Fundamental
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samples for the study. Further development will be granted by the dialog with advanced atomistic simulations (ab initio and tight-binding) carried out in the laboratory and the lively context offered by
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, are needed. Specific expertise can focus on modelling of e.g., polymer, biomolecular systems, or colloidal systems. We work at both atomistic and coarse-grained modelling levels and appreciate multiscale
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. As a member of the Stenlid lab, you will be exposed to a broad range of computational methodologies, ranging from atomistic and electronic-structure–based materials modeling and characterization, via
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techniques such as in-situ and time-resolved spectroscopies/microscopies as well as rheological measurements on different length scales. Experiments are accompanied by modelling from the atomistic level to
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composition and atomistic modeling of materials. The main activities will include: - formulating new descriptors of critical temperature (Tc) incorporating electronic fluctuation effects, evaluated by
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deformation in situ. Nat. Mater. 23, 20–22 (2024) [2] Erbi, M. et al., Tuning elastic properties of metallic nanoparticles by shape controlling: From atomistic to continuous models, Small, 2302116 (2023) [3