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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
engineers detect faults earlier, track system degradation, and make better-informed maintenance decisions. But how can we turn this complex information into something reliable, explainable, and actionable
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for 36 month fixed term at 0.6 FTE (22 hours). Key Accountabilites Organising intervention sessions and data collection, including set up, implementation and analysis of the SleepBoost intervention program
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by the Ada Lovelace Centre and the University of Birmingham. This interdisciplinary project is ideal for candidates with a background in physics, materials science, chemistry, or computational science
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an increasingly complex development environment. Areas to consider that impact the modelling are: Framework Language Process How wide / how deep i.e. what do we model and why? How much provides a good answer i.e
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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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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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Application deadline: 15/08/2025 Research theme: Computer Science No. of positions: 1 Eligible for: UK This 4-year PhD project will be funded by DLA studentship and is open to UK students
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, integrating genetic, clinical, and demographic data for national research and trials. Establish high-fidelity MUC1 sequencing using long-range PCR and ultra-deep nanopore sequencing to resolve the complex VNTR
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fantastic opportunity for ambitious computer scientists to join our Computer Science Graduate Teaching Assistant (GTA) Programme! How does it work? Candidates will study for a four year, full time funded PhD
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essential to determine how these models can be made lightweight in terms of computational complexity, memory footprint, and energy consumption for deployment on edge devices or constrained gateways