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and is a leading multidisciplinary research-intensive technology university delivering economic, social and cultural benefits. For more information please visit: https://www.brunel.ac.uk/about/our
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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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letter (maximum 2 pages) and your CV (maximum 2 pages). Please make sure that your cover letter and CV provide adequate information on your academic ability, research potential, communication and
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/developing-people-and-skills/stfc/training/studentship-information-for-students/payments-to-students/ ). An additional Research training support grant totalling £5,000 is available for the duration
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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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the harmful effects of deepfakes on ordinary people. You will draw on methods from psychology, linguistics, data science, and computer science, such as behavioural analytics, neuroimaging, face and voice
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, and flow cytometry. You’ll work closely with other members of the lab to analyse data, interpret results, and contribute to ongoing publications. You will also be responsible for maintaining accurate
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to apply For further information please contact: Name: Dr Francesco Fanicchia Email: Francesco.fanicchia@cranfield.ac.uk If you are eligible to apply for this studentship, please complete
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academia and industry. Uncover and quantify critical degradation mechanisms to inform the design of next-generation fusion materials. Translate sophisticated scientific data into impactful insights through
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creatively. Good computer skills, plus good presentation and writing skills in English, are required. Previous research experience in contributing to a collaborative interdisciplinary research environment is