43 natural-language-processing-intern Fellowship positions at UNIVERSITY OF SOUTHAMPTON
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the project forward and translate our research into tangible innovations for the UK’s growing photonics sector, building upon our recent work published in Nature (https://www.nature.com/articles/s41586-025
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to have strong quantitative skills and experience of working with large gridded geospatial datasets. They will focus on designing approaches to process and utilise such datasets in population modelling and
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ageing processes, high voltage electrical testing, analytical and simulation techniques. You will report to the sponsor at regular meetings, and be responsible for preparation of regular reports
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Directives from the Mass Observation Study, University of Sussex. Qualitative narratives were collected in Spring 2023 and also August 2024 in order to investigate the role of intergenerational support in
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-intensive institutions. With a strong international reputation for research, teaching, and enterprise, we are proud holders of an Athena SWAN Silver award. Part of the School of Healthcare Enterprise and
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: high voltage engineering, dielectric materials, materials ageing processes, high voltage electrical testing, analytical and simulation techniques. You will report to the sponsor at regular meetings, and
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the area of environmental assessment, including life-cycle assessment, with a strong publication track record in high-quality international journals A willingness and ability to help with the supervision
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designed to fulfil the requirements for an out-of-programme experience for a specialist trainee in oncology, haematology surgery, pathology or any other disciplines related to cancer, but may also be
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the University to support their professional development and project delivery. This role is based full-time at Ingenium Biometric Laboratories in Canterbury, Kent. Due to the nature of the research and the lab
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collaborative nature of the programme. Based within the Data-driven Biology Group, the postholder will develop and validate AI and data science tools for multi-cancer risk prediction models using population-scale