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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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AI hardware beyond traditional computing architectures. Gain a unique combination of skills in mathematics, machine learning, and photonics. Be part of a multidisciplinary research team spanning
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work — and how to design better ones. Why apply for this PhD? Work on the next-generation AI hardware beyond traditional computing architectures. Gain a unique combination of skills in mathematics
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Application’. Use ‘Course Search’ to identify your programme of study: Search for the ‘Course Title’ using programme code: 8080F Research Area: Applied Mathematics Select ‘PhD Mathematics’ as the programme of
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operators links classical observables (functions on phase space) with quantum operators. Microlocal analysis also provides essential tools to rigorously define, compute, and analyse resonances, which describe
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’ to identify your programme of study: Search for the ‘Course Title’ using programme code: 8080F Research Area: Applied Mathematics Select ‘PhD Mathematics’ as the programme of study. You will then need
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j.m.warnett@warwick.ac.uk Essential and Desirable Criteria Essential : First degree (Batchelors and/or Masters) in Mathematics, Computer Science, or field with strong mathematical focus. An interest in signal
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Knowledge, Skills and Behaviours Demonstrable experience in quantitative or computational modelling Strong programming skills (e.g. R, MatLab, or similar) Ability to develop and analyse mathematical
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-world datasets throughout, and collaborating with the non-profit organisation Earth Rover Program. What You'll Gain This is a chance to do original, high-impact science at the intersection of mathematics
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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