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different neurons in the neocortical circuit and use them for closed-loop brain stimulation. By examining how these spatiotemporal dynamics relate to behaviour, you will develop new brain decoding methods and
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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variants of importance sampling. We will connect these methods to modern formulations of Monte Carlo algorithms to improve their accuracy, scalability, and overall computational cost. The methodology so
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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may decide to implement a same format slightly differently, leading to irreproducible results, non-portable code, hard-to-find bugs, and other unexpected behaviours. On the backdrop of this complex
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technologies. Agricultural applications present a unique opportunity for AI systems as they often involve repeatable tasks within a relatively low-safety-risk environment, unlike public or transportation
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. It will use signals from different sources—such as radio signals and internal sensors— to maintain robust and accurate PNT, even when satellite signals are weak or missing. A built-in intelligent
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design that is applicable to different types of energy harvesters. This project will explore how PMC can be optimised to maximise efficiency, reliability and scalability using novel circuit topologies
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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of recycled 6xxx Aluminium alloys subjected to different thermomechanical treatments” BCAST is a specialist research centre in metallurgy with a focus on processing of metallic materials