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methods/simulations, state-of-the-art computational techniques (e.g. data-driven methods and/or FEM) and/or theoretical material modeling will be given preference We offer: chance to collaborate with
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theories and numerical methods, carrying out and analysing field and remote sensing observations and conducting and analysing numerical model simulations. The PhD position is funded by the German Research
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on methods development in machine learning, uncertainty quantification and high performance computing with context of applications from the natural sciences, engineering and beyond. It is embedded in
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involve a numerical simulation component. Your tasks analyzing measurements of ocean turbulence using autonomous glider vehicles use and develop machine learning methods to describe ocean turbulent fluxes
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breakage models, e.g. with stochastic tessellations Development and implementation of estimation methods for the model parameters, e.g. with machine learning or statistical methods Lab work and collection
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of the (computational) mechanics of solids and the finite element method and/or spectral solvers Practical experience in at least one programming language (preferably Python) and experience with the use of Unix/Linux
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, geomagnetism) and the development of corresponding numerical methods. We offer the opportunity to work in a small interdisciplinary research group consisting of mathematicians, computer (geo)scientists, and
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Your Job: Explore bio-inspired algorithms through simulation—both numerical and circuit-based—and experiment with existing hardware, including CMOS and memristor circuits. Additionally, will need
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Some experience with numerical simulations such as the Finite Element Method (FEM) and Multi-Body Simulation (MBS) is a plus. We offer: a fascinating understanding at mobility in general with a
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professional networking opportunities A structured PhD program with a comprehensive range of continuing education and networking opportunities - more information about the PhD program at the HZDR can be found