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interests, describing how past experience and future plans fit with the advertised position and the project. Interview date if known: November 3-7, 2025
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experience; the coherence, importance, and viability of the proposed research; and its relevance to the project; and fit with supervisorial strengths at Durham.
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assessed upon: Motivation and career aspirations Potential and intellectual excellence Suitability for specific project Fit to FLOOD-CDT Please familiarise yourselves with FLOOD-CDT before applying. During
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://flood-cdt.ac.uk . Please note, that your application will be assessed upon: (1) Motivation and Career Aspirations; (2) Potential & Intellectual Excellence; (3) Suitability for specific project and (4) Fit
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more frequent and intense extreme rainfall events, creating serious challenges for flood risk management across the UK. Current rainfall datasets are not fit for purpose: radar estimates can be
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experience, candidates are expected to have strong teamwork and collaboration skills, as well as competency in critical and independent thinking. You’re a good fit if: you have experience in machine learning
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, this will be confirmed via a formal studentship award letter; this will be provided separately from any Offer of Admission and will be subject to standard checks for eligibility and other criteria.
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& Intellectual Excellence; (3) Suitability for specific project and (4) Fit to FLOOD-CDT. So please familiarise yourselves with FLOOD-CDT before applying. During the application process candidates will need
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) Motivation and Career Aspirations; (2) Potential & Intellectual Excellence; (3) Suitability for specific project and (4) Fit to FLOOD-CDT. So please familiarise yourselves with FLOOD-CDT before applying
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, and viability of the proposed research; its relevance to the project; and fit with supervisorial strengths at Durham.