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Field
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-Based Modelling ✔ Data Science & Advanced Analytics with real-world SCADA data ✔ Renewable Energy Systems & Wind Turbine Engineering ✔ Industry Engagement & Research Commercialization ✔ Scientific Writing
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, finance, and healthcare, where data integrity and system reliability are non-negotiable. This PhD project addresses the integration of robust security measures within AI-enabled electronic systems
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Award summary 100% fees (UK home only), a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate), and a research training support grant of £20,000. Overview This PhD project is part
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This fully-funded PhD research opportunity, supported by EPRSC Doctoral Landscape Awards (DLA) and Cranfield University offers a bursary of £22,000 per annum, covering full tuition fees. This PhD
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Research theme: Applied Mathematics, Continuum Mechanics, Liquid Crystals Application deadline: All year round The successful candidate will join the PhD programme of the Department of Mathematics
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Eligibility Criteria A minimum 2:1 Honours degree or international equivalent in a subject relevant to the proposed PhD project (such as mathematics or theoretical physics) is our standard entry, however we
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Requirements We will only consider candidates with a good Bachelor’s degree (ideally, a first, minimum 2:1) and/or a master’s degree in computer science, data analytics, health economics, or computational
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and work independently, excellent analytical skills and strong verbal and written communication skills are also essential requirements. How to apply You must apply through the University’s Apply
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collaborative project that spans multiple continents. You will contribute to the development of new chronobiological analytics on existing data, design experiments to collect novel chronobiological data, engage
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staff and more than 6 PhD students. See https://www.nottingham.ac.uk/mathematics/research/mathematical-neuroscience.aspx for further information. The positive research environment fostered by the School