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Field
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quantitative species detection for in-field use. This innovative approach will miniaturise complex molecular workflows, enabling field-based, real-time species monitoring without the requirement for laboratory
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computational approaches towards a new project which seeks to better understand the causes and consequences of the correlation between multiple traits and to quantify trait variation that arises from new
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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
of next generation agentic AI systems. In this PhD programme, you will redefine how the world works, learns, and discovers, turning bold ideas into tools used by millions. You will then become one
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for one of our information sessions , and to download the application form . The QUARTILES Doctoral Landscape Award (DLA) is a BBSRC and NERC-funded research and training programme designed to equip PhD
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for high frequencies due to loss and dispersion limitations. Tackling these problems with complex equalization techniques will not be possible because of their high-power consumption and needed area. To
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areas, including the Fens and Romney Marshes, depend on complex networks of drains, rivers, and pumps to regulate water levels. These drainage catchments are crucial for protecting homes, sustaining
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challenges which experimentalists must consider – computer simulations of molten salts are therefore a very valuable guide to efficient experimentation. Molten salts have been well-studied using classical
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for complex data accessible to the scientific community and to produce innovative methodology related to trial designs, longitudinal and event history data, precision medicine, causal inference, AI/machine
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gardens and sponge fields, are biodiversity hotspots that deliver critical ecosystem services through their complex structures. However, they face increasing threats from fishing, resource extraction, and
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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical