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56 Faculty of Mathematics Startdate: 01.09.2025 | Working hours: 20 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 31.08.2028 Reference no.: 4200 The Faculty
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teachers, with 45 holding senior professional titles), including 10 high - level talents such as provincial outstanding young talents, 2 national excellent instructors for mathematical modeling, 1 excellent
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, Physics, Geosciences or a closely related field Experience with mathematical inverse methods, global geo-/paleomagnetic field modelling expertise is an advantage Knowledge of geomagnetic field evolution
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Max Planck Institute for Plasma Physics (Greifswald), Greifswald | Greifswald, Mecklenburg Vorpommern | Germany | about 2 months ago
-Institute for Plasma Physics in Greifswald offers within the division Stellarator Reactor Studies a PostDoc-position for a Physicist or Engineer (m/f/d) for the development of computational models
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in the Mathematical Institute (https://www.maths.ox.ac.uk/groups/mathematical-biology/infectious-disease-modelling ). The postdoctoral researchers will develop data-driven mathematical models and
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and providing guidance to PhD students who are actively involved in ecohydrological modeling research. - Conduct laboratory analyses and field work. - Collaborate with local researcher from the college
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the project include mathematical derivation, analysis, and comparison of models, methods, and simulation approaches; rapid prototyping of new ideas in custom code; implementation of new models, methods, and
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-term carbon cycle and over the coming century. This PDRA position will focus on model approaches to quantifying CO2 exchanges associated with chemical weathering associated with the warming cryosphere
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scaling and generalization behavior Roll out the model to the global user community Requirements PhD or MSc in computer science, physics, mathematics or a related discipline Experience with large-scale HPC
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with