13 postdoctoral-composite-structure PhD positions at Chalmers University of Technology
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We are searching for a doctoral candidate eager to take part in crossdisciplinarity work within battery technology for a sustainable future. This work will compose both theoretical and experimental work. A model is to be developed to estimate the material mass breakdown for various cell designs...
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Assessing how dissolved organic matter and microbial community composition affect OMP removal Investigating the spatial localization of OMPs and their transformation products within biofilm and GAC matrix
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challenge-driven with a systems-based approach and requires interdisciplinary efforts, which is reflected in our team's composition spanning engineering, natural and social sciences. It is a dynamic and
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of on-site construction production processes, as well as sustainable development. You will also demonstrate independence, creativity, and strong collaboration and analytical skills. Research environment
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focus on organic semiconductors, polymer blends and composites. The group develops new plastic materials for wearable electronics and energy technologies, including organic solar cells, thermoelectrics
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We are looking for a highly motivated, skilled, and persistent PhD student with experience in computational fluid dynamics (CFD) and some knowledge in structural analysis. The research aims
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activities are focused on the modelling of the mechanics of structures, components, and processes along with involved materials, thereby providing mechanics-based solutions and virtual solution tools to our
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construction. Information about the research environment The PhD student will join the research environment Architecture, Media, and Material Practice (AMMP) at the Department of Architecture and Civil
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behavioural, organizational, and ergonomic factors—such as discomfort—may contribute to traffic-related risks. Through close collaboration with stakeholders in the healthcare, construction, and technology
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-resolution 3D microstructures from microscopy data Learn meaningful representations of complex material structures The work contributes to both scientific understanding and sustainable industrial innovation