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simulation and AI-supported data analysis are central tools. The work is carried out at the Department of Fibre and Polymer Technology and in collaboration with FOI and industrial partners. Qualifications
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of the system is still insufficiently understood. This project investigates the underlying fluid-structure interaction mechanisms and develops advanced numerical methods for high-fidelity simulation
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operational safety levels of track and vehicles. Here, the project will take a hybrid approach in combining physical simulations and data driven analyses (featuring AI/ML as well as ‘traditional’ statistical
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equivalent foreign degree, obtained within the last three years prior to the application deadline Experience with simulation frameworks, system-level performance evaluation, or machine learning, is highly
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the link between mechanics and biology in the musculoskeletal system, including related pathologies and repair of skeletal tissues. Experimental studies, tissue characterisation and computational simulation
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professional experience and knowledge. (max 2 pages) Copy of diplomas and grades from your previous university studies. Translations into English or Swedish if the original documents have not been issued in any
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to the instructions in the ad. The application must include: CV including relevant professional experience and knowledge. Copy of diplomas and grades from your previous university studies. Translations into English or
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are responsible for ensuring that your application is complete according to the instructions in the ad. The application must include: CV including relevant professional experience and knowledge. Copy
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manufacturing systems that strengthen operational robustness, improve resource efficiency and raise the quality of decision-making. The research will investigate how simulation-based optimization, digital twins
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, simulation, manufacturing systems, 5G/6G, decision support and real industrial demonstrators. The overall ambition is to demonstrate significant reductions in costs arising from uncertainty, risk and variation