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, along with an aptitude for developing new experimental techniques that relate to this exciting research program. To be successful with your application, you will need to demonstrate: An awarded PhD in
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
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drivers, and how do these intersect to create wet and dry extremes? How can improved representation of SM variability at process scales enhance monitoring and prediction, benefitting SM-dependent
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. Although this approach has led to the development of alloys such as Type 316, Alloy 617, 800H, and 709, the process remains slow, expensive, and inefficient. Creep-fatigue represents a complex interplay of
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and translation. You will be based in the School of Electronics and Computer Science (ECS), working alongside an interdisciplinary team led by Dr. Shelly Vishwakarma (s.vishwakarma@soton.ac.uk), in