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welds. Modelling and simulation: development of a physics-based simulation framework (e.g., phase-field modelling) to predict hydrogen-assisted crack growth and long-term mechanical integrity of steels
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of four partners in SpinENGINE project. The SpinENGINE project aims to create a new approach to computing based on emergent properties, i.e., complex, non-linear behaviour in tunable ensembles
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and temporal scales. Through this research, you will gain a better mechanistic understanding of these relationships as a basis for predicting future changes related to management decisions and climate
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engineering and natural systems and develop predictive tools for mechanical failure. Our team is highly interdisciplinary and international, bringing together researchers with backgrounds in materials science
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the environmental impacts of processes and energy systems, we develop predictive methods for Life Cycle Assessment. Our technological focus is thermal energy systems, sustainable carbon feedstock, and CO2 capture
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experimental methods. Develop and apply methods for demultiplexing, normalization/QC, effect-size estimation, biological inference, and predictive modeling. Contribute to biological manuscripts and methods