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Field
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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conditions. The specific aims are: To optimise large-scale production of a high-value carotenoid compound that is naturally released in nanoparticle form by a marine alga. Develop a mechanistic understanding
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that rotations play in gas-surface collisions. Working within a well-supported and experienced research group, the student will join and further develop a unique Magnetic Molecular Interferometer (MMI) apparatus
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define observable events based on expert knowledge and available evidence. Development of a post-race analysis structure, process and data ‘toolkit’ that can build on historical understanding of race
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into their structure. However, we don’t yet know how to design these complex printed parts and we are still developing new leading-edge materials to grant them new capabilities. Advantages: In this PhD studentship, you
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to develop novel, bio-inspired neural networks that flexibly and robustly control locomotion in multi-limbed robots. "Self-organised clocks for reliable spiking computation" (Supervisor: Prof Timothy O'Leary
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high-priority condition as new disease-modifying therapies are developed. This PhD tackles a key diagnostic bottleneck in ADTKD-MUC1 and integrates precision genomic medicine into routine kidney care
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vibrant research and development team, collaborating closely with our industry partners; Costain, National Highways, DfT and our spin-out, Didimi, and domain experts to contribute to the development of a
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coalitions for delivering reliable, low-carbon energy services. Collaborating closely with UK Power Networks, SSE Energy Solutions, and the University of East London, you will develop robust economic Model
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The transition from the traditional relative perspective in engineering design and product development (“Is design A better than design B?”) towards an absolute sustainability perspective (“Is the