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, specifically battery prototypes. What you will do Multiscale modelling to better understand RFB behavior and identify optimal hierarchical shaped pore- and electrode-structure to encounter optimum electrolyte as
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latest issues that impact our society and are offering you the chance to actively help in shaping the change! We offer ideal conditions for you to complete your doctoral degree: Supervision and support by
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 25 days ago
Institute for Demographic Research (MPIDR), in Germany, subject to MPIDR terms and conditions. The role is based within the Mortality and Inequalities Research Group at LSHTM with close partnership with
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Modelling" (department “Geodesy”), we are looking for a: Reference Number 10727 We offer a position for the research project 'Advancing the understanding of glacial isostatic adjustment in Antarctica' (ANT
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institutions. Scientists from all over the world encounter excellent conditions for their work in their own research field and in interdisciplinary networks alike. The BMC is located on the Martinsried Campus
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implementation of modeling approaches and empirical analyses Publication and presentation of research results in relevant journals and at (international) conferences Supervision of student seminar papers and
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and transfer of science to society. As a modern employer, it offers attractive working conditions to all employees in teaching, research, technology and administration. The goal is to promote and
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excursions. The PhD student will work on analysing the reliability of paleomagnetic records, deriving uncertainty estimates, and building time-dependent models of the paleomagnetic field evolution using a
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the change! We offer ideal conditions for you to complete your doctoral degree: Competent and interdisciplinary working environment, as well as an excellent framework in the areas of experiments and modelling
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on the following tasks with either with a stronger model-development or application focus: Design knowledge-graph-augmented transformers and retrieval-augmented generation (RAG) pipelines that enable