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Fully Funded PhD Position: Decoding Chromosome 1 Risk in AMD Using Stem Cell–Derived Retinal Models Host: Newcastle University (UNEW), UK Consortium: MSCA Innovative Training Network Pandora Start date
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project aims to address this gap through the development of a rigorous empirical framework for evaluating the security robustness, failure modes, and operational risks of AI decision engines in cyber
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innovative and dynamic sector, estimated at more than £100 billion and growing at over 6% every year. This project aims to deliver a step-change in hair care technology by developing new strategies to form
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£100 billion and growing at over 6% every year. This project aims to deliver a step-change in hair care technology by developing new strategies to form covalent bonds within hair fibres, moving beyond
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the spatial distribution of stomach bugs and antibiotic resistance are linked to other risk factors. It will use national data to: Map how infections and resistance change across time and regions. Explore how
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models and observations yet still rely heavily on precomputed risk maps. Deep learning has improved flood mapping, but many models remain event-specific and transfer poorly between regions. Geospatial
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the security robustness, failure modes, and operational risks of AI decision engines in cyber‑physical environments. Impact and Relevance The proposed research directly addresses challenges faced by industries