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imagination for atomistic structure and dynamics; an interest in fundamental science with real-world applications; and both the initiative to work independently and the skill to collaborate in a
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characterise the internal dynamics of neural networks. Topological approach – based on metrics derived from topological data analysis to capture qualitative structural changes in the neural network configuration
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project investigating mechanosensing in Diptera. This post will focus on using detailed wing geometry models and kinematic measurements in computational fluid and structural dynamics simulations to recover
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dynamic environment. You will be supervised and mentored by Dr Kaili Rimfeld and Dr Dan Anderberg, with training tailored to your career goals. We are particularly interested in candidates with: A strong
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materials. Practical experience in fabricating 2D materials and a deep understanding of their structure-property relationships are highly desirable. You should also have expertise in advanced characterisation