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to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show
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-edge advancements in automated drug discovery through the integration of high data-density reaction/bioanalysis techniques, organic synthesis, laboratory automation & robotics and machine learning
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developed. This project is available from 1st October 2025. Applications accepted until post is filled. Informal inquiries can be made via email to Prof. Chris Bennett (c.bennett@nottingham.ac.uk
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the PhD. The Faculty has outstanding facilities and works in partnership with leading industrial partners. Please contact Mohammad Reza Ilkhani ezzmi1@exmail.nottingham.ac.uk for further information and an
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of £3,000. Starting date will be preferably on 1st October 2025. Home students are strongly encouraged to apply. Please send your CV (including publications if apply) and transcripts to Dr Ke Li (ke.li2
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Manufacturing processed NAB material and any post-processing requirements to match and/or exceed the properties of traditional cast/heat-treated NAB. You will have the opportunity to develop a Digital
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—quality post-graduate research development and training environment of the University of Nottingham. This PhD scholarship is offered in collaboration with the UKRI funded transdisciplinary hub
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is, in general, a challenging problem and one for which there is relatively little data, because experimental chemistry takes time and is expensive. Within our research group, we have a highly
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key area of patient safety that can be improved with the use of computer vision approaches to system analysis. For many clinical procedures there can be multiple deviations in service delivery, which
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be