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Field
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About the Role You will develop and apply novel computational methods to quantify the societal impact of fundamental science discoveries. Candidates close to completion of their PhD will initially
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the Project HOPE 1000 pregnancy cohort, a large, longitudinal study based in Durham, North Carolina, to investigate how prenatal and early-life environmental exposures influence immune-related outcomes during
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are not designed to produce reliable regional estimates of those phenomena. Therefore, small area estimation (SAE) methods are used. With technological advances, Big Data now offers valuable spatial
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interpretation of atmospheric circulation in high-resolution reanalysis data, idealised model simulations and a state-of-the-art weather forecasting system. The post-holder will have the opportunity to teach
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
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involve conducting large-scale data synthesis projects to better understand the drivers of urban metacommunities and biodiversity patterns. In particular, the lab is interested in understanding the drivers
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software development, and has leading roles in the ATLAS High Luminosity Large-Hadron Collider (HL-LHC) upgrade (Silicon Strip detector, Liquid Argon calorimeter, and Trigger & Data Acquisition). The group
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using experimental data from laboratory setups Validate models through targeted measurements and structured testing procedures Analyse loss mechanisms and system efficiencies under various operating
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associate to support an ethical, legal, and social implications (ELSI) study aim of the NSF funded study “Integrating Human-Derived Neural Networks and AI for Information Processing in Brain Organoids” under
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular