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the right one for you! This is a fully funded PhD position to develop micromechanical models of high-pressure die-cast aluminium, a unique opportunity for a motivated individual to work in a collaborative
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We are looking for a PhD candidate fascinated in modelling erosion processes in sensitive clay slopes. The highly sensitive clays, called quick clays, can change from solid to liquid with small
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work. A model is to be developed to estimate the material mass breakdown for various cell designs and cell formats. The model will be validated from teardown analysis of commercial lithium-ion battery
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this overlooked impact. The turbulent wake governs spreading of pollutants from ships, influence the air-sea gas exchange, and may act as a barrier, affecting connectivity in the marine ecosystem. There is an
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and development Generative AI models for sound, music, visuals, 3D graphics, or movement Projects related to Generative AI Background in mathematics and statistics of Deep Learning What you will do
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responsibility is to conduct high-quality research on hybrid artificial intelligence. You will: Combine deep learning to capture long-term patterns and uncertainties with stochastic model predictive control
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and responsible development of the maritime industry. We address the multiple pressures that ships pose on the ocean and try to bridge the gap towards environmental management and marine spatial
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of quick clays. A novel combination of miniaturised thermal-hydro-mechanical experiments and particle level modelling will be pursued to unravel the unique mechanisms that make quick clays so hazardous and
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utilized to mitigate flooding risks through hydrological modelling and stakeholder engagement.Focusing on the Gothenburg region, the project will: Identify roads suitable for climate adaptation in three
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in fluid dynamics, turbulence modeling, CFD, and turbomachinery. Experience with CAD and CFD tools (e.g., Ansys Fluent, CFX, StarCCM+, OpenFOAM). Programming skills (e.g., Python, MATLAB). Knowledge