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About the role - The role-holder will be proficient at quantitative analyses and be support the wider inter-disciplinary research team in analysing quantitative data captured from a variety of
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Risk Management, Governance, Operational Resilience (Business continuity and Incident Response), Information Security and Compliance, Insurance Services and our Academic Quality Assurance provision
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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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processing large amounts of information. For students identified by the system as being totally non engaged, you will also be required to work across multiple platforms and systems to check other sources
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processing large amounts of information. For students identified by the system as being totally non engaged, you will also be required to work across multiple platforms and systems to check other sources
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to modern slavery in conflict settings. This attempt requires a large, interdisciplinary team working within a cross-cutting framework to connect vast amounts of data and answer many fundamental questions
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to modern slavery in conflict settings. This attempt requires a large, interdisciplinary team working within a cross-cutting framework to connect vast amounts of data and answer many fundamental questions
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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging
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to modern slavery in conflict settings. This attempt requires a large, interdisciplinary team working within a cross-cutting framework to connect vast amounts of data and answer many fundamental questions
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to modern slavery in conflict settings. This attempt requires a large, interdisciplinary team working within a cross-cutting framework to connect vast amounts of data and answer many fundamental questions