18 research-assitant-in-composites PhD positions at Chalmers University of Technology
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to departmental duties, including teaching and lab assistance. Discover more Find more general information about doctoral studies at Chalmers here . About the research environment The Division of Electric Power
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We are looking for a highly motivated PhD student to join the research group of Professor Christian Müller . The focus of the project is on understanding the mechanical properties of conjugated
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with GKN Aerospace Sweden with partial work there and combines numerical and experimental research. Project overview The purpose of this project is to contribute to the development of an ultra-efficient
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our research team for addressing a timely societally relevant problem. Project overview The aim is to unravel the mechanisms, and time scales involved at particle scale, for the formation and failure
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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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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department
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We invite applicants to join our team of researchers within the area of maritime environmental science. We are looking for a PhD student to work on cumulative risk assessment of shipping pressures
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We invite applicants to join our team of researchers within the area of maritime environmental science. We are looking for a PhD student to study turbulent ship wakes and their effects on the marine
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failures. We offer access to unique experimental data and computational tools developed by our research team for addressing a timely societally relevant problem. Project overview The aim is to unravel
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control