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Field
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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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intensity of these changes. This PhD project will ultimately enable aircraft to reroute safely and efficiently in real time as weather evolves. By merging scientific machine learning, large-scale data
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simulation workload and update the solver data structures when the mesh changes. These approaches would be applied on modern large-scale heterogeneous parallel computing environments where both CPUs and GPUs
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. Yet, many stellar and planetary parameters remain systematically uncertain due to limitations in stellar modelling and data interpretation. This PhD project will develop Bayesian Hierarchical Models
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(R1) Positions PhD Positions Country United Kingdom Application Deadline 30 Nov 2025 - 23:59 (Europe/London) Type of Contract Temporary Job Status Full-time Job Status Extra Information PhD postion
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technology (FinTech) Payment technologies and the future of money Explainable artificial intelligence (AI) in financial services Integration of FinTech and big data in financial markets and sustainable finance
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technologies and the future of money Explainable artificial intelligence (AI) in financial services Integration of FinTech and big data in financial markets and sustainable finance. To discuss the entry
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writing and implementing code alongside extracting information, trends, and patterns from large datasets. Topics to explore during this PhD project include: Investigating available software options Methods
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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