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Field
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to a breakdown in ecosystem function, including impacting the integrity and complexity of trophic interactions (e.g. food webs). Cumbria Connect aims to recreate woodland pasture ecosystems across large
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generating coherent text, mimicking human-like conversations, and completing complex language tasks such as translation and summarization. However, despite their powerful generative capabilities, these models
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sub-populations within rural areas, such as children and older adults, face even greater disparities highlighting the importance of an intersectional lens in understanding these complex challenges
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to complex challenges in this field. Essential and Desirable Criteria Solid foundation in computing principles, particularly computer graphics and machine learning. A 1st or 2.1 undergraduate (BEng, BSc, MEng
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uncertainty and dynamic conditions. In complex electronic systems, ensuring reliability and minimizing downtime are critical challenges. AI-driven fault diagnosis and self-healing electronics offer innovative
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uncertainty quantification for robust structural design, particularly for complex aero-engine systems with limited experimental data. Recent work by the University of Southampton developed a novel data driven
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experts in academia, industry, and clinical settings will provide valuable networking opportunities and insights into real-world applications, preparing the student for a successful career in healthcare
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real-world challenges. We work with an extensive network of industrial partners including BT, DataSparq and Tesco. Engage with our network of charitable partners Students have the opportunity to engage
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analysis. They will also be equipped to conduct independent, complex experimental/numerical research projects. Entry Requirements A very good undergraduate degree (at least a UK 2:1 honours degree, or its
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aforementioned tasks with the following actions: Develop the principles and theories for governing the scalability principles for building innovative robotics end-effectors that can access geometrically complex