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shift in the world of hardware design. On the one hand, the increasing complexity of deep-learning models demands computers faster and more powerful than ever before. On the other hand, the numerical
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to rapidly acquire new skills (E) Attributes and Behaviour Ability to analyse and reflect on own performance, seeking advice where necessary (E) Willingness to travel to research sites off Newcastle University
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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at highest risk of kidney function decline, aiding trial prioritisation What you will learn and why it matters This PhD provides a rare skill set sought after in academia, biotech, and healthcare innovation
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, opening in autumn 2025 in the heart of Gloucester. Housed in the fully renovated former Debenhams building in Kings Square, this vibrant campus will be a hub for teaching, learning, and community engagement
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participants Ideally, practical skills in one of (a) programming, (b) machine learning, and/or (c) design Responsibilities Developing and conducting novel research projects individually and on teams Developing a
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systems safer, more efficient, and more sustainable. The aim of this project is to design a smart cognitive navigation framework that information from various sensors and learn to make decisions on its own
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for innovative solutions to improve worker well-being. The project proposes a novel, integrated framework leveraging virtual reality (VR), the internet of things (IoT), and machine learning (ML). Workers will
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, adaptive control strategies, and hybrid energy storage solutions to address key challenges in self-powered systems under dynamic environmental conditions by: Develop machine learning or heuristic-based
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untapped potential remains in extracting value from this data. This PhD will explore advanced analytics techniques, including machine learning, digital twin modelling, time series analysis, spectral analysis