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Field
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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and diffusion of gases/vapours. This project will investigate and develop methodologies for understanding the key relationships between fundamental materials properties (degree of crystallinity, extent
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vulnerabilities like side-channel attacks and unauthorized access, which can compromise system integrity. Developing robust security measures within AI-enabled electronics is essential for applications in defence
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range of disciplines for the development of future aerospace technologies and capabilities. During the PhD programme there will be regular reviews and presentation opportunities as well as the chance to
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The role The post is part of the Wellcome Discovery Award research programme “Collective Action for Race Equity in Health and Social Care”, which aims to address and dismantle structural factors
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project offers a unique opportunity to develop autonomous microswimmers, which are bioinspired structures at the micrometre scale that can propel themselves through fluids, mimicking natural swimming
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Award summary 100% of home tuition fees paid and an annual stipend (living expenses) of £20,780 Overview Interested in developing new experimental systems for previously unknown disease mechanisms
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potential later start dates.) Supervisors: Professor Gwyneth Davies, Professor Rich Fry (Swansea University) and Professor Jenni Quint (Imperial College, London) Aligned programme of study: PhD in Population
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the development of specialized hardware architectures capable of efficient, real-time processing. Embedded AI hardware architectures, including neuromorphic processors and low-power AI accelerators
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, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking opportunities. How to apply