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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing
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for cardiovascular disease in this patient group using linked electronic health record data. The post offers an excellent opportunity to develop expertise in risk prediction methodology for electronic health records
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the use of satellite data for monitoring inland and coastal water quality across Scotland. We anticipate that the successful candidate will spend around one third of their time on the Forth-ERA project
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data analysis methods for fitting of mathematical models to single cell data. Your working environment will be in the Zeeman Institute (SBIDER) https://warwick.ac.uk/fac/cross_fac/zeeman_institute/ and
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and analyse field data, contribute to high-impact publications, and present findings at conferences and workshops. Collaborate and Engage: Work closely with industry partners, participate in project
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includes embedded and sensing systems, tinyML, data science, AI and software development. Responsibilities encompass active involvement in the ProSensing project's development activities, such as AI on Edge
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mobilisation activities. You will play a key role in conducting document analysis and semi-structured interviews with a range of participants, analysing qualitative data, and co-leading participatory workshops
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for cardiovascular disease in this patient group using linked electronic health record data. The post offers an excellent opportunity to develop expertise in risk prediction methodology for electronic health records
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portfolio of translational and clinical research studies, including real-world data generation, biomarker sample collection, and data analysis. They will also be actively involved in the clinical delivery
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exciting project that will develop new approaches to handle missing data in statistical analyses based on machine learning methods. The Research Fellow will be based in the Department of Medical Statistics