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understanding of geomagnetic field evolution across different timescales, including both stable and extreme periods. This will involve working with data-based models and numerical dynamo simulations
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develop data flows and methods for utilizing the data in simulation models. We are particularly keen to appoint a data-savvy researcher with strong Python and SQL skills to lead data integration, curation
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of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts are supported by
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properties (k, cp) as f(T) Particle Finite Element Method (PFEM) simulations Co-ordination of collaboration with project partners Evaluation, compilation and presentation of results, documentation, preparation
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optimizing simulation tools such as CalPhad to support experimental findings. Conducting in-depth metallographic analysis and establishing correlations between mechanical properties and microstructural
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, or in information quality for decision-making. Are skilled in quantitative analytical methods, and ideally have some experience with simulation techniques. Research tasks Review and assess technologies
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-evolutionary simulation. The position is available from 1 March 2026 or as soon as possible thereafter and is for 2 years. Qualifications and competences Applicants must have a PhD degree or equivalent or have
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physics and condensed matter theories to address the problem of fracture in complex materials. You will be working with experimental model systems and numerical simulations of materials that exhibit
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potassium channels Simulation of electrophysiology experiments Please indicate in your application which of the above-listed projects is most intriguing for you. Your profile Successful candidates have strong
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surrogate models that approximate complex physical and biological systems traditionally modeled by PDEs or other computationally expensive simulations. By incorporating physical priors such as conservation