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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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, large-scale biomedical datasets, including UK Biobank and the CPRD. It will integrate complex longitudinal data—including harmonized EHRs, genetics, and the novel features captured by the LLM—to generate
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, and changing how water and sediment move through large rivers. While these impacts are becoming clearer, what remains poorly understood is how long such disturbances last and, critically, how
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research as a doctoral student you will be passionate about using large-scale data to address important questions in cancer research, have strong experience of quantitative analyses, and be a positive
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4 Nov 2025 Job Information Organisation/Company The University of Manchester Department Computer Science Research Field Computer science » Computer systems Researcher Profile First Stage Researcher
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understood. However, the increasing availability of high-resolution satellite imagery now enables the creation of detailed large-scale, multi-temporal inventories, offering new opportunities to investigate
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overuse injuries. Wearable sensors to quantify of the impact and benefit of sleep on the recovery, performance and overall wellbeing of athletes. Using big data and machine learning methods to identify
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(e.g. neural ODEs and SDEs), identifiability and interpretability, large language and sequence models, and multimodal data integration. This position will be based at the world-leading CRUK Cambridge
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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