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Field
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the central challenge hindering this vision: the fundamental incompatibility between text-native LLMs and the operational reality of computer networks. Directly applying LLMs is impeded by three core technical
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degree of oxidation. The scope of this project would be to design a methodology for capturing material property and gas transport data, gather data on these materials and subsequently build up
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), machine learning (ML), deep learning (DL) and Data science methods for medical image analysis, to autonomously grade the fundus images from large datasets. This will be supported by Professor Neil Vaughan
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. Research Methodology: Representative samples and field structural data will be collected from a number of accessible sites across the Cornubian batholith. Discrete samples will be fully characterised
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data from saltmarsh and mangrove estuaries. Evaluate the impacts of restoration design decisions in real estuary settings. Compare multiple estuaries to assess how context influences restoration outcomes
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an advantage. English language requirements: Applicants must meet the minimum English language requirements . Funding information: The studentship is for 3 years and provides a minimum tax-free stipend
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, leaving users vulnerable to data misuse and cyber attacks. Current AI-based security tools often act as “black boxes,” generating alerts without explanation, undermining users' trust and slowing adoption
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programming skills. Expertise in developing computer vision and machine learning algorithms would be desirable, highly motivated and enthusiastic about advancing AI for societal impact. Qualifications A high
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: Applicants should have, or expect to achieve, at least a 2:1 honours degree (or equivalent) in a relevant subject, typically in the physical sciences or engineering. Experience of computer simulation, or
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include a research proposal aligned with one or more of the following priority areas: Research Themes Multiphysics and data-driven constitutive modelling of traumatic brain injury and its long-term impact