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Field
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and machine learning methodology to help deal with key challenges in developing such models in large-scale observational electronic healthcare record data. These models will be applied to important real
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the low volumetric density of hydrogen, ammonia has emerged as a promising hydrogen carrier and zero-carbon fuel. The overall aim is to develop a novel direct ammonia fuel cell technology that can
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, public health, behavioural science, epidemiology, data science, psychology, sociology, or related fields. Curiosity, initiative, and willingness to work across disciplines are essential. Training and
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Project Overview Resilient and productive agriculture is reliant on bespoke planning involving data-driven decisions guided by local practice, required practice, local data, such as crop yield, and
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backgrounds such as AI, computer vision, computer graphics, machine learning, robotics, wearable technologies, textile engineering, fashion technology, digital fashion, or related areas are encouraged to apply
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knowledge graph from scientific papers and cognitive test questionnaire data, and second, to integrate the graph with transformer-based large language models and causal learning. This offers an explainable
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information to an attacker. Funding These are doctoral teaching assistant positions that combine a PhD programme with a university teaching contract. Your time will be split approximately 60% on research and 40
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measurement data. The project combines fundamental research with practical engineering challenges, offering opportunities to contribute to technologies with real-world industrial impact. This project provides
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Brushless Doubly Fed Machines (BDFMs) are emerging as a promising technology for offshore wind turbine generators due to their fractional-sized power converters, elimination of rotor brushes and
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expert advice, analysis and capability across a wide range of applications including Robotics & Autonomous Systems, AI and Data Science. Eligibility and Desired Background Applicants should hold (or expect