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that can anticipate and adapt to the behaviour of humans and other autonomous agents. This PhD project aims to investigate the integration of Theory of Mind (ToM) reasoning into autonomous agents to improve
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three coupled components. First, a physics-informed graph surrogate model will emulate network hydraulics at scale, representing pipes and assets as a graph and predicting flows, depths, surcharge
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geolocated social media data, and computational techniques from network science and machine learning. It is interdisciplinary, combining theories of healthy and accessible cities with computational data
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across disciplines An independent, self-motivated approach to research You'll gain skills spanning dynamical systems theory, data science, earthquake science, and soil ecology, working with large, real
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computational project where you will use a variety of methodologies to produce hierarchal 3D lattice structures, e.g. first principles calculations (density functional perturbation theory), molecular dynamics