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new Wellcome-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will benefit from the extensive and broad
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for their employability in applications. Additionally, machine learning methods need to be applicable to high-dimensional and to noisy data that are typically encountered in real-world applications. The aim of this project
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. You will focus on machine learning, but will be involved in all areas. There are also spinout opportunities. For details: PhD information sheet The team have wide experience studying bumblebee behaviour
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the investigation and realization of improved microwave probe design, data processing, and visualization techniques to provide a robust method of data analysis, flaw characterization and sizing. AI/machine learning
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and kinematic models with machine-learning-based channel state information (CSI) prediction to enable robust, low-latency connectivity across multi-layer NTN systems. This PhD project sits
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), computation (bioinformatics, machine learning, statistical analysis), working with animals (radio-tracking, animal handling/sampling), and deep knowledge of evolutionary biology and gerontology. The Norwich
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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modes (e.g., HCCI) for net-zero fuels like hydrogen and ammonia. A key innovative pillar is the development of an AI-driven control strategy. Machine learning algorithms, including reinforcement learning
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built to identify and correct errors, apply bias adjustments, and assess data quality. State-of-the-art multisource blending methods will then be applied (e.g. kriging, probabilistic merging, machine
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on the performance of the CMF; Using machine-learning (deep learning) methods to develop a predictive model and conduct the sensitivity study to investigate the multiple factors on the performance of flow meter