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. English language requirements: Applicants must meet the minimum English language requirements. Further details are available on the International website . Funding information: The studentship is for 3-years and
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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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/applicants/english/ ). Funding information: The studentship is for 3 years and provides a tax-free stipend of £20,780 per annum for the duration of the studentship plus tuition fees at the UK rate. Due to
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listed in the job description. Click here for information and advice on writing an effective Supporting Statement. Please do not attach any manuscripts, papers, transcripts, mark sheets or certificates as
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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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for this vacancy and to view further information about the role, please click the 'Apply' button above. We reserve the right to fill the position with a qualified candidate prior to the conclusion of the advertising
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A PhD studentship is available to work on Logistics automation. The student associate will work in the Intelligent Logistics Group within the Distributed Information and Automation Laboratory (DIAL
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, biotechnology or a related field. Applications will be considered from candidates who are working towards or nearing completion of a relevant PhD qualification. Please contact Vladimir for more information
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reconciliation, enhancement, and integration of the MLGB dataset, working with legacy print, manuscript, and digital sources. You will apply and adapt digital methods (especially TEI XML), analyse provenance data