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Field
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distribution can predict both single AZ and whole synapse function at the neuromuscular junction (NMJ). Adapt and convert an existing, experimentally validated MCell simulation of mammalian NMJ AZs into Python
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collection methods for external data (e.g. web scraping) to collect data for use in modelling and analysis. Develop analytic plans, engineer supporting algorithms, write new functions or applications in
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computational tools for quantifying electromagnetic field distributions down to the fundamental atomic scale. The project will build on recent developments in inverse scattering methods, including ptychography
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literature. Foundational Algorithms for AGI AGI will not emerge from scaling existing models alone; it requires a new algorithmic foundation for learning, reasoning, and adaptation. This research area is
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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A PhD studentship is available to work on Logistics automation. The student associate will work in the Intelligent Logistics Group within the Distributed Information and Automation Laboratory (DIAL
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A PhD studentship is available to work on Logistics automation. The student associate will work in the Intelligent Logistics Group within the Distributed Information and Automation Laboratory (DIAL
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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developing new methods and techniques that will improve standard ML algorithms so as to achieve good performance outside their training distribution, by treating high-dimensional problems as an explicit
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, including: asymptotic enumeration of (hyper)graphs with highly irregular degrees; distribution of small subgraphs in random (hyper)graphs with highly irregular degrees, and extensions of these considerations