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represented include: fluid mechanics, biomechanics, statistics and data science, computational mathematics, combinatorics, partial differential equations, stochastics and risk, algebra, geometry, topology
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and skills transfer between disciplines, organisations and sectors structured, skill-based training high-quality working conditions personal career support equal opportunities For more information see
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: Prior experience with analysis of observational remote sensing data sets and/or numerical model output related to cloud properties is desirable. Strong computational skills, and ideally experience with
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interpreting 3D seismic and well data is a requirement, preferably using Petrel. Experience with quantitative earth science and modelling is an advantage. Experience of salt tectonics is an advantage. Experience
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flow law, compare it to similar research on olivine, and help implementing this model into the geodynamic software ASPECT. The aim is to develop a single method for anisotropic flow modelling for both
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broadband and spectrally resolved measurements of cloud radiative properties and assist with flying a tethered balloon platform. The successful candidate will use the collected data to investigate the impact
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three years with research duties exclusively. The hired candidate will be admitted to the PhD program in Social Sciences. The education includes relevant courses amounting to about six months of study, a
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for mental health issues based on their genes and environment. The tools and data created will be shared to help other scientists study and address these important issues. The position(s) will be
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research training leading to the successful completion of a PhD degree. The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application to the PhD