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to develop, because all of the features associated with the small- and large-molecule drug components must be optimised together. Computational mathematical modelling is used to make the optimisation of ADCs
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a lack of a coherent and mathematically rigorous methodology for how health, environmental and population exposure and vulnerability data can be combined to optimally issue warnings in order to
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Application deadline: 27/03/2026 Research theme: Applied Mathematics, Thermal-Fluid-Dynamics, Multi-Physics UK only This 4 year PhD project is fully funded and home students. The successful
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mathematically in their full multiscale complexity, many complex systems leave warning signals in their data - subtle mathematical fingerprints that appear before a rapid transition unfolds. But reading those
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will develop new mathematical tools to analyse brain imaging data using persistent homology, a method from topological data analysis (TDA) that captures the shape and connectivity of complex data across
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models of the neonatal brain. The successful candidate will work on the intersection of neuroscience and new computational methods, combining mathematical and biophysical models with state-of-the-art
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completeness. In other instances, where sufficient data do exist, the models used in attempts to glean performance insight may be overly simple and violate mathematical or statistical assumptions or be overly
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operation. This is an exciting PhD project with industrial collaborators at the intersection of power systems, artificial intelligence, and mathematical modelling. The project is well-suited to students with
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for applicants with a degree in Computer Science, Mathematics, Physics, or Engineering. Prior experience in AI is necessary. Prior experience in tomographic imaging and medical physics would be advantageous but
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Research Assistant or Associate in Operator Algebras to work with Dr Chris Bruce in the School of Mathematics, Statistics and Physics at Newcastle University. This position is full time for a duration of 24