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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
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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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, neuroscience and personalised medicine. The Department of Biomedicine provides research-based teaching of the highest quality and is responsible for a large part of the medical degree programme. Academic staff
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and staff, and providing support in applying for additional research grants. There is also opportunity to conduct analyses of already-collected data. Job Description Primary Duties & Responsibilities
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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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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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generating, mobilising, and harvesting “big data” to create a dynamic and agnostic collection of information and deliver a new class of research that will enable a better understanding of the clinical
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generating, mobilising, and harvesting “big data” to create a dynamic and agnostic collection of information and deliver a new class of research that will enable a better understanding of the clinical
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with partners across Europe: data sharing, code exchange, joint publications and reporting. Your qualities You hold a PhD (or near completion) in Soil Science, Environmental Modelling, Biogeochemistry
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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in