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Do you have experience with modelling structures subjected to dynamic loading? Are you interested in data-driven methods for modelling applied loading? Are you eager to share your knowledge within
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. The position focuses on frequency-domain electromagnetic (FEM) and transient electromagnetic (TEM) methods. The successful candidate will contribute to the development of an inversion framework for the joint
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strong permanent magnet. To investigate this, you will use and further develop numerical methods in our state-of-the-art open source micromagnetic model, MagTense. At present, our ability to model
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patterns, and extreme climate events remains a subject of debate. Using a combination of climate modelling, statistical methods, and machine learning, ArcticPush aims to uncover the conditions under which