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Field
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by climate change affect local fuel properties and ecosystems. Different vegetation distributions can lead to very different fire spread mechanisms, as well as different effects on structures. In
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" (Supervisor: Prof Timothy O'Leary) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic
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optical setup construction. They will make use of commercial simulation software to test electromagnetic designs, algorithmic coding to design metamaterials, fabrication techniques to produce
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. road, power distribution). This project will develop new insights into what drives flooding and extreme wind to co-occur on timescales from (sub-)daily to seasonal. Our recent work suggests that
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optical setup construction. They will make use of commercial simulation software to test electromagnetic designs, algorithmic coding to design metamaterials, fabrication techniques to produce
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behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help of the simulation tool To support in the development and
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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
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-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
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PhD Studentship: The Role of O-glycosylation of the Stalk Region of the Immunoglobulin Receptor GPVI
to determine their effects on GPVI signalling. In addition, super resolution microscopy will be used to determine how glycosylation effects the distribution of GPVI on the cell membrane. Finally, nanobodies will
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interact without full trust in a centralized party. This research project aims to develop cryptographic solutions and frameworks that secure AI systems, particularly in decentralized and distributed settings