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Supervisors Dr. Yinhao Li Eligibility Criteria You must have/expect to gain, minimum 2:1 Honours degree/international equivalent in a relevant subject to the proposed PhD project. A solid background in computer science
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select ‘PhD Computer Science’ as programme of study You need to provide the following information in ‘Further Questions’ section: ‘Personal Statement’ (mandatory) - upload document or write statement
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PhD studentship in Computer Science: From Formal Requirements to Specification-based Automated Testing for Safety-Critical Medical Device Software Certification Award Summary 100% fees covered, and
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PhD studentship in Computer Science - Dynamic Validation of AI Systems in Digital Twins: A Real-Time Safety Framework for Critical Infrastructure Resilience Award Summary 100% fees covered, and a
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Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate). Additional project costs will also be provided. Overview The Internet of Things (IoT) and Edge Computing are undergoing a major transformation. Systems that once relied heavily on...
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that respects both user preferences and legal requirements. Your research will create it. What makes this different This isn't a typical PhD. Through structured industrial secondments (several weeks yearly
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PhD Studentship in bioinformatics and cardiovascular biology - Exploring the application of geocomputational methods to high resolution spatial transcriptomics data from the human heart Award
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the home fees and international fees. Overview Interested in bioinformatics, and high-resolution mapping of human heart? This PhD project will investigate how computational geography methods can be scaled
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PhD Studentship: Rooted in Resilience: Optimising the Plant-Soil System for Flood-Resilient Rain Gardens Award Summary This studentship provides a tax-free annual living allowance £26,546 plus a
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approaches that overlook plant ecology and the interaction with soil structure development. This PhD project will transform rain garden design by linking plant traits to hydrological and ecological outcomes