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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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-value reinforcements in their short and randomly aligned form. A key challenge to the effective reintegration of recycled carbon and glass fibres into high-performance products lies in achieving scalable
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functionalise these chitinous polymers with the aim of enhancing the biofilm functions. The successful candidate for this project will focus on achieving the above objectives and attending the NBIC training
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cells or the tumor microenvironment reduces tumor growth and extends survival in preclinical models, underscoring their potential as dual-function therapeutic targets. To address this, we aim to develop
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research area, and work alongside your peers for the first 10 weeks of your studies, splitting your time between high-level training and laboratory rotations. You will also take part in a three-month
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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 challenging properties of uncertainty, irregularity and
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use this formalisation to encode our STV algorithm on encrypted ballots. This approach aims to ensure both the correctness and privacy of the tallying process, paving the way for verifiable and secure
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will work on the design, development, and testing of integrated systems that may include laser generation and stabilisation, RF control, PID systems, and embedded electronics. The work aims to improve
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research area, and work alongside your peers for the first 10 weeks of your studies, splitting your time between high-level training and laboratory rotations. You will also take part in a three-month
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Demonstrator’s role: In addition to meeting the requirements of a PhD research student, demonstrators will be expected to spend a minimum of 144 hours per year to education activities commensurate with