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are especially challenging to represent in numerical models of the atmosphere. Clouds affect the Earth’s radiation budget. Changes in their properties, either due to global warming or aerosol pollution, can
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. Project description This PhD project focuses on advancing the scientific computing foundations of quantum spin dynamics by developing efficient numerical algorithms for modeling complex, open quantum
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of emissions of greenhouse gases. The reason for most of this uncertainty is that clouds are especially challenging to represent in numerical models of the atmosphere. Clouds affect the Earth’s radiation
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for efficient last-mile deliveries with a focus on climate and flexibility. Using advanced modeling and data analysis, you’ll create solutions that make final deliveries smarter and more sustainable. Your work
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has gone through a very rapid development in the last few years. Large-scale machine learning models are however notoriously over-confident. With insufficient amounts of data to train them on together
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atmospheres, their origin and how they are expected to evolve in a changing climate. Spectral 2D and 3D numerical solvers based on spherical harmonics will be used for the project to perform simulations aimed
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and approaches, as well as implementations that can be practically used. The first project targets specifically numerical programs that appear widely in e.g. safety-critical (embedded) systems, data
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on developing a fundamental understanding and numerical models for multiphase flows, which are crucial for various industrial processes. The successful candidate will develop advanced physics-based methods in