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-plastic bonds and finally the inertial aspects will be defined in order to define and solve the equations of motion of systems consisting of thousands of degrees of freedom. Where to apply Website https
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composites for enhanced durability, performing microstructural analysis and mechanical testing. Topology Optimization & AI Integration: Use AI and machine learning to guide structural and topology optimization
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attention to phenomena dependent on strain rate, temperature, thermal history, and microstructure; elasto-viscoplastic and micromechanical constitutive modeling, developed in academic and/or industrial
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. The position spans electrochemical testing, modeling, microstructural analysis, and collaborative research in an international environment. Your primary tasks will be to Conduct degradation studies to uncover
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solid oxide fuel cells. The project will span length scales, from materials discovery, including with computational approaches, through mechanical properties and microstructure optimisation
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The University of Birmingham is seeking to appoint a Research Fellow to contribute to the creation of knowledge, in terms of chemistry and microstructural effects on the radiation tolerance and integrity of fusion
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian Key Responsibilities: Responsible for new carbon material-enhanced
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: - 1 Associate Research Professors whose research project pertains to the study of structural or microstructural properties in a laboratory that maintains strong connections with large-scale research
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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 2 months ago
and ML-based constitutive modeling, finite element technology, and microstructural simulation tools. This position is ideal for candidates who enjoy working in a research environment, building high
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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 2 months ago
that combine classical phenomenological constitutive models with neural-based components. Training data will initially rely on synthetic datasets generated from high-fidelity microstructural simulations