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‑bounded turbulence. This short, intensive 9‑month position offers an exciting opportunity to advance fundamental turbulence research using DNS/LES and data-driven optimisation techniques. In this role, you
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the network, and every synapse is updated, on every epoch. Recent work has begun to challenge both halves of this independently. Progressive Data Dropout has shown that progressively reducing the training set
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provide considerable training in chronobiology, signal transduction in plants, microbiology, and data analysis and interpretation. As part of the “MicroClock” programme funded through an ERC Synergy grant
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planetary systems. The project will investigate Probabilistic Numerical Computation for large scale Inverse Problems, with a particular focus on cases governed by Partial Differential Equations (PDEs). Recent
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emergence of large-scale quantum computing poses a significant threat to current public-key cryptographic schemes (e.g., RSA and ECC), creating an urgent need for quantum-safe security solutions. This PhD
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support massive Internet-of-Things (IoT) deployments through technologies such as network slicing. At the same time, the emergence of large-scale quantum computing poses a significant threat to current
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- 2025 - Business Strategy and the Environment - Wiley Online Library Additive Manufacturing: A Comprehensive Review Big data, machine learning, and digital twin assisted additive manufacturing: A review
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an annual tax-free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be paid. Robotic metal additive manufacturing offers transformative potential for flexible, large-scale, and high
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methods to accelerate the discovery of better catalysts that use less platinum and have improved long-term stability. By combining large-scale density functional theory with machine-learned interatomic
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, is strongly associated with physical activity levels, and is a cause of significant disability. PhD description: To address this we have a large cohort study running. We are looking for a dynamic