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position focused on developing ultra-lightweight and ultra-conductive carbon-metal composites. The selected candidate will contribute to multidisciplinary research advancing next-generation metal-based
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the Institute for Sustainable Energy and the Environment. This position will oversee composite manufacturing trials, optimize process parameters, and apply advanced materials characterization techniques to assess
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qualifications and experience. Area of expertise: Thermoplastic composite materials, composite material durability, test methods for composite materials, composite materials manufacturing, experimental
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Department Description Position Location Main Campus FTE 1.0 Job Summary Contributes to the end-to-end development of polymer-based dental implants by integrating material innovation, additive manufacturing
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of the pilot system, including development and review of PFDs, P&IDs, and related documentation. Contribute to safety and risk assessment activities, such as HAZID and HAZOP workshops. Participate in Factory
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Chalmers University of Technology focused on the recycling of carbon fibre composites. The project aims to develop a novel method for recovering fibres using magnetic fields, with the goal of lowering
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Engineering or related, with strong experimental mechanics research. Expertise in polymer/composite additive manufacturing. Proven high-impact publications. Excellent technical, experimental, and communication
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of the pilot system, including development and review of PFDs, P&IDs, and related documentation. Contribute to safety and risk assessment activities, such as HAZID and HAZOP workshops. Participate in Factory
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industrial demands in the wood composite industry. In this project, you will have the opportunity to combine cutting-edge expertise in polymer science with practical solutions for a greener future. If you have
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Post Doctoral Researcher in Human-Centered AI for Software Engineering, Department of Electrical ...
of responsible and human-centered AI in software engineering (AI4SE). The AI4SE1DK project addresses urgent industry needs by investigating how Large Language Models can be effectively, ethically, and sustainably