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mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
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, process stability, and the downstream consolidation and performance of remanufactured composites. This fully-funded PhD project fits within a wider research programme with industrial partners and an
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Closing Date Sunday 17 August 2025 Reference PHD002-25 A funded PhD position is available on a project funded by the Leverhulme Trust. Description below: The density of information content in screen media
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Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM) at the University of Nottingham. The student will work in
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Applications are invited for a PhD project within the University of Nottingham’s Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM). The student will work in
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is characterised by complex and highly dynamic turbulent flows that define the performance and design of renewable energy systems and their infrastructure. This PhD project aims to enhance
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, to industrial catalysis and green energy production. This PhD project offers a rare opportunity to explore hydrogen surface collisions at a fundamental, molecular level to gain unprecedented insight into the role
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spectrum of neurological symptoms. This PhD project will explore how mTOR dysregulation drives glial activation, complement-mediated CNS injury and neural circuit dysfunction. Using organotypic brain slice
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supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
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also be opportunities in the wider community of researchers at UCL to develop new networks. This is a fixed-term role for 6 months in the first instance, with the possibility of extension (3 years in