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hydrogen, ammonia, methanol and advanced biofuels into vessel operations while maintaining performance, safety and reliability. This PhD project will develop lifecycle and systems‑level models that track
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systems with "self-diagnosis" and "self-healing" capabilities. By integrating federated learning, graph neural networks, and blockchain technology, we will develop a framework that moves beyond static
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biology approaches to develop rapid, low-cost, and field-deployable tests for detecting quarantine pests/pathogens. You will evaluate technologies such as CRISPR-based systems, strand displacement reactions
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have implications for food security and conversation. The successful student will explore innovative synthetic biology approaches to develop rapid, low-cost, and field-deployable tests for detecting
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‑related pathways, long‑distance wind‑borne dispersal may also represent a significant introduction route for insects. This project aims to develop and apply quantitative methods to assess wind-borne
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dispersal may also represent a significant introduction route for insects. This project aims to develop and apply quantitative methods to assess wind-borne dispersal risk for a range of pests of concern to GB
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programme that will train the next-generation of doctoral carbon champions who are renowned for research excellence and interdisciplinary systemic thinking for Net Zero. The ReNU+ vision is that they will
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motivated, creative, and curious PhD candidate excited to bridge disciplines and co-develop this research. You will join a collaborative and internationally active Regenerative Engineering Group, with scope
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. This PhD project will investigate how biofouling affects the hydrodynamic, thermal and fluid-structure interaction performance of dynamic flexible cables and develop novel engineering solutions to enhance
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accountably. This is where you come in. Your mission Working at the intersection of privacy research and real-world engineering, you'll design and build a computational stewardship engine—an autonomous agent