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, and how strain rate influences material behaviour. The resulting experimental data will be used to validate numerical models and contribute to certification by analysis of future composite structures
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. Nonlinear finite element modelling and characterisation Conduct numerical modelling via nonlinear finite element analysis and physics-informed neural networks Materials characterisation for soft, textile and
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through the MARUM - Center for Marine Environmental Sciences - is offering the position of a Research Assistant (PhD student position) (f/m/d) in German pay scale 13 TV-L with 75% of the weekly working
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through the MARUM - Center for Marine Environmental Sciences - is offering the position of a Research Assistant (PhD student position) (f/m/d) in German pay scale 13 TV-L with 75% of the weekly working
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Challenge: Extreme water events threaten people and infrastructure Change: Understand impact dynamics with experiments and numerical simulations Impact: Optimize the design of resilient
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staff members (researchers, engineers, PhD students) and operates several major experimental facilities: LULI2000, Apollon, HERA, XCAN. The PhD student will join LULI's theory team (TIPS) and will work
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understand, explain and advance society and the environment we live in. Your role The PhD student will work under the guidance of a professor on a research theme and will also contribute to education in a
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Chair of Biological Imaging 13.08.2026, Academic staff Join us in shaping the future of biomedical imaging We are looking for a PhD student (f/m/d) who wants to take ownership of the software
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has numerous collaborations with leading biomedical research groups in Norway and abroad. This PhD position is also embedded in an international research environment with co-supervision across
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
environment for managing large ensembles of numerical simulations, applied to sensitivity analysis [Terraz et al., 2017] and meta-model learning [Meyer et al., 2023]. The Datamove team has also contributed