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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 2 months ago
simulation to reduce the real-to-sim gap; (ii) estimating each mechanism's performance and its sensitivity to variation in design or manufacturing parameters, such as used material, prototyping technology, or
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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lenses. Investigate fluid transport, sensing capabilities, and material behaviour within hydrogel-based microsystems. Publish your research in leading scientific journals and present your work
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. Candidate Profile Applicants should hold a Master's degree in Materials Science and/or Computational Methods in Mechanical Engineering (or a closely related field). The successful candidate should have: a
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that communicate dynamically in specific tissue niches. Our laboratory has an interest in resolving the interactions between tissue-resident immune cells, with the overall goal of identifying key mechanisms that can
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, research and education at the ME faculty focusses on fundamental understanding, design, production including application and product improvement, materials, processes and (mechanical) systems. ME is a
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, see Section 6-1 of the PhD regulations for more information You must have a relevant Master's degree in mechanical and industrial engineering, chemical engineering, chemistry, and materials science or
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understanding, design, production including application and product improvement, materials, processes and (mechanical) systems. ME is a dynamic and innovative faculty with high-tech lab facilities and
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PhD Position - Operando X-ray Characterization of Catalytic Interfaces for Chemical Hydrogen Storage
-equilibrium processes” focuses on dynamic processes that take place out of equilibrium conditions. In particular, we are interested in resolving the molecular reaction mechanisms (under near-reaction conditions
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are developing a suite of models to deliver a through-process microstructural and mechanical property prediction framework for steel. By integrating these models into a cohesive digital twin architecture, the work