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quantification for greater accuracy and reliability. Material failure is a critical area of study in engineering, as understanding how materials behave under stress is essential for designing safe and reliable
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background in psychology, neuroscience, cognitive science, or a related discipline, and a keen interest in cognitive computational neuroscience. You will join a vibrant and supportive research team with access
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their reliability in predicting long-term material performance. Ultimately, the goal is to provide a computational tool capable of simulating the behaviour of polymeric materials under real-world conditions, helping
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Applications are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in manufacturing engineering. The successful candidate will be based
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II CDT) at the University of Warwick, where you’ll be immersed in a community dedicated to computational science innovation. With expert training in atomistic simulation, machine learning, and high
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will acquire Electronic structure theory calculations of materials, atomistic molecular simulation methods Experience with machine learning methods Expertise in surface science characterization