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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
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format. This will allow combinations of neural networks with physics models. The project brings together PhD students and senior researchers from multiple disciplines to tackle challenges in sustainable
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with expertise in materials characterisation, computer vision, computational modelling, and machine learning. The other PhD positions connected to the project are: PhD Student Position in Generative
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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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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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Computational Arts, Music, and Games within the DSAI division. About the research project This position is related to investigating learned cultural representations in data search spaces of generative AI models
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Master’s degree in Applied Mechanics, Mechanical Engineering, or a closely related field. Strong knowledge of fluid mechanics, CFD, turbulence modelling, and structural mechanics. Understanding
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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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qualifications Marine biogeochemical processes Hydrodynamic processes related to ships, turbulence, or mixing Oceanographic modelling Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary
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Materials Science are found in the areas of: Human-Technology Interaction Form and Function Modeling and Simulation Product Development Material Production - and in the interaction between these areas