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of Engineering and Materials Science, a large School with approximately 70 academic staff and around 45 postdoctoral research staff. There are around 1000 undergraduate and taught postgraduate students and 220 PhD
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computational biologists, immunologists, clinicians, and experimental scientists, you will support study design, data interpretation, and reporting, and contribute to the development of robust, reproducible
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concurrent programming will be particularly desirable. You should have a PhD in experimental High Energy Physics and have the potential to be a leader in the field. Experience with software, computing
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should hold a PhD (or be close to completion) in a relevant analytical and quantitative discipline, such as civil or transport engineering, transport modelling, mathematics, statistics, data science
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a specific context, conduct individual research, analysing detailed and complex qualitative and/or quantitative data from a variety of sources, and generate original ideas by building on existing
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for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria 1. PhD awarded in physics, applied
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optimization of large language models (LLMs) and related architectures for generative tasks, continuous learning, indexing or retrieval, support of retrieval augmented generation over many data points from long
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analysis. Secure and maintain research ethics approval and manage data in line with University policy, funder requirements and applicable data protection law. Maintain transparent and reproducible research
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data infrastructures and have the ability to use some data science methods. About the Candidate The successful candidate must have a PhD in infrastructure studies, data science or related fields, and
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and interpreting data, and communicating results to academic and industrial collaborators. You will also contribute to publications and presentations and provide guidance to junior members