13 component-labeling-agorithm-cuda Postdoctoral research jobs at Chalmers University of Technology in Sweden
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. This unique position combines advanced finite element modeling, machine learning, and experimental studies, while offering the opportunity to contribute to open-source libraries and collaborate directly with an
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-source computational tools in a project that aims to create life-saving technology to prevent devastating skull fractures in elderly populations. This unique position combines advanced finite element
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, and environmental sustainability. As a postdoc, you will become part of a dynamic team that offers a stimulating and flexible work environment, with opportunities for collaboration and networking both
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benefiting from the ongoing digitalization of society. Our research emphasizes social, economic, and environmental sustainability. As a postdoc, you will become part of a dynamic team that offers a stimulating
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We are looking for a Postdoc to become part of our team at the Division of Subatomic, High-Energy and Plasma Physics at the Department of Physics. Join our innovative team and contribute to exciting
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-14158 Is the Job related to staff position within a Research Infrastructure? No Offer Description We are looking for a Postdoc to become part of our team at the Division of Subatomic, High-Energy and
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degradation to the molecular characterization of biomass polymers and their conversion into functional materials. As part of your role, you will also contribute to a Horizon Europe project focused
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Functional Materials, 2024, 34, 2406875). This project will further develop this technique with a focus on aerospace applications such as lightning protection, de-icing, and sensing. This position is part of
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electromagnetic processing. The work involves close cooperation across several departments. You will have access to a well-equipped experimental environment and be part of a collaborative team dedicated to creating
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knowledge base. Main responsibilities include: Conduct benchmarking and further development of risk assessment models and components. Investigate the reliability of accident data, including cross-validation