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imaging, based on absorption, provides good image contrast between high- and low-density materials, such as bones and soft tissue. However, it cannot distinguish subtle density differences between soft
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while inferring underlying physiological changes. Required knowledge Machine learning, dynamical systems theory, control theory, signal processing, time series analysis, neuroscience are all relevant and
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), singular optics, using electrons, atoms and light and the exploration of complex systems using statistical field theory. "Catastrophes on order-parameter manifolds" (with Dr Alexis Bishop and Dr Timothy
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networks that can be trained to do machine learning and AI tasks in a similar way to artificial neural networks. In this project you will develop machine learning theory that is consistent with the learning
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Creating efficient and beneficial user agent interaction is a challenging problem. Challenges include improving performance and trust and reducing over and under reliance. We investigate
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What makes a machine conscious? This PhD would be at the intersection of Philosophy, AI and neuroscience. You would study the latest neuroscience based theories about how consciousness emerges in
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Advisory System, or data from other implantable or wearable devices. This involves consideration of both feature-based machine learning or data science approaches and neural mass parameter estimation
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My area of expertise is condensed matter theory. I am interested in the interplay between interactions and unconventional electronic properties of novel materials including graphene, topological
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My research focuses on the theory of strongly correlated phenomena in cold atomic gases and electron systems. Particular topics of interest include low-dimensional quantum systems, superconductivity
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programming. An ability to code in C, C++ or Rust is also necessary. Candidates with experience or interest in column generation, cutting planes, polyhedral geometry and graph theory are especially invited