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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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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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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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, 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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1 November 2025 to 31 October 2028. Who we are: The Independent Research Group Receptor Biochemistry harnesses the complex interplay between proteases and receptors during plant-pathogen interactions
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research environment. Project background Future European power systems are expected to be driven by a very high share of renewable power plants and will be extremely complex, uncertain environments with
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is funded from 1 November 2025 to 31 October 2028. Who we are: The Independent Research Group Receptor Biochemistry harnesses the complex interplay between proteases and receptors during plant-pathogen
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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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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