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Field
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necessarily require formal education in geotechnics. Applicants with a background in mechanical/materials engineering or alternatively mathematics/computer science with an interest in numerical modelling
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capabilities in reasoning, planning, and generalisation, acquired through extensive pre-training, provide the foundation for a true cognitive engine capable of managing network complexity holistically
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
is to exploit transformer-based attention mechanisms to model sequential dependencies and capture long-range interactions, making them promising tools for complex spectrum management. Despite being
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significantly enhance their capacity for self-management, leading to more reliable, efficient, and trustworthy systems in safety-critical and complex domains. On-the job research training for the Doctoral
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Testing (NDT) – a crucial technique used in industries to assess materials, components, and structures without causing damage. This PhD project focuses on advancing Ultrasound Testing and X-ray Computed
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industrial SBSP experts, the candidate will explore the nonlinear structural dynamics of LSSs to fully understand the complexity of their control. They will use this foundation to explore idealised and
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hard to model with classical computers, it presents a valuable opportunity – to use quantum technologies to efficiently model and simulate other complex systems. Recent focus has been on how we can more
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About the Project The future power grid will be a highly complex cyber-physical system, integrating multiple distributed energy resources (DERs) such as solar, wind, marine, and bioenergy alongside
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practical applicability. Whilst most research projects on this topic are restricted to the use of synthetic Li-bearing brine samples, which do not accurately reflect the complex geochemistry of real brine
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dynamic mobility network to better capture the complexities of disease spread. The project focuses on two core objectives: Adaptive surveillance: designing policies that actively allocate testing resources