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manufacturer and technology company. Applications are invited for a 3.5-year EPSRC funded UDLA PhD studentship. The studentship will start on 1st October 2026. Project Description As Deep Learning and
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) and define the problem mathematically. Secondly, a central component of the PhD will be to learn mappings between heterogeneous spaces through latent-variable models and representation learning. Some
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interdisciplinary team with clinicians and engineers; You have strong programming skills in Python; You have knowledge of medical image processing, and machine learning and deep learning techniques; Written and
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Doctoral Researchers (PhD students) to work on deep learning methodologies for machine and robot perception. These positions are funded by the Horizon Europe project OPERA (Open Perception, Learning, and
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training programme at the start of the PhD to develop skills in areas such as programming, data analysis, machine learning and signal processing. This will provide the technical foundation required to work
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using existing NPL datasets. The work will integrate suitable physics-based models (for example PV performance modelling, electro-thermal and thermofluid dynamics) with deep learning and multi-fidelity
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investigate deep learning architectures capable of learning microstructure-property mappings, including convolutional neural networks for microstructure image analysis, graph-based representations
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expected to learn basic R or python to generate plots and analyze data. Qualifications Requirements for employment are: You have deep knowledge of immunology including autoimmunity You have experience
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. Melodia, SIA: Symbolic Interpretability for Anticipatory Deep Reinforcement Learning in Network Control, IEEE INFOCOM 2026 [3] A. Duttagupta, M. Jabbari, C. Fiandrino, M. Fiore, J. Widmer, SymbXRL: Symbolic
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applied methodologies in Data and Image Analysis, Computational Imaging, Statistical Learning, Uncertainty Quantification, Robust Estimation, and Deep Neural Networks. The group combines expertise in