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Environment - Wiley Online Library Additive Manufacturing: A Comprehensive Review Big data, machine learning, and digital twin assisted additive manufacturing: A review - ScienceDirect Full article: Achieving
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, neuroscience, machine learning, or related fields and/or merit/distinction-level performance in a relevant postgraduate degree (e.g. MSc) Experience of working in a neuroscience, clinical or engineering research
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accelerators originally designed for artificial intelligence. These accelerators achieve exceptional performance by using low precision arithmetic, which is sufficient for machine learning tasks but much too
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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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and other asset classes Financial econometrics and machine learning. Corporate finance and accounting Corporate governance and shareholder value Corporate finance, networks and insider trading Market
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for complex data accessible to the scientific community and to produce innovative methodology related to trial designs, longitudinal and event history data, precision medicine, causal inference, AI/machine
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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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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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by detecting and predicting threats such as pests, diseases, and environmental stress in line with the UK Plant Biosecurity Strategy. The project harnesses computer vision, deep learning, and large
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? This PhD project offers a unique opportunity to apply machine learning to solve a critical engineering challenge within the railway industry. The Challenge: Rail grinding is a crucial maintenance activity