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science with bioinformatic component. Experience working with high performance computing (HPC) with large data sets is essential. Experience with pipelines for genomic sequence analysis from raw reads. Relevant
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high-impact research in a collaborative, interdisciplinary environment spanning medical statistics, epidemiology, clinical microbiology, and data science. You’ll work with large-scale electronic health
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present network performance data based on your specialist knowledge. This role requires deep expertise in large-scale WAN networks, particularly those leveraging SD-WAN technologies, to meet the strategic
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modelling, quantification of uncertainties and data analysis. They will work closely with a large delivery team at the UK Centre for Ecology & Hydrology, British Geological Survey and Imperial College London
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engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early
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Research Fellow in Intervention Development to join the Big Data in Health Grou About us Our big data in health team at the University of Southampton is based in the Primary Care Research Centre. We
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, engineering and mathematics. You would be working with world-leading computer science researchers in computer architecture, systems, cybersecurity, machine learning and many other topic, each with interesting
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. This position is in the team led by Dr James Hay, based at Old Road Campus in Headington. You will be responsible for conducting detailed analysis of a large immunological dataset, including data from ELISA, PNA
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a visionary leader to head our high-performing Transformation Office and drive large-scale change across our complex University. Reporting to the SVP Operations and COO, you will work directly with
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, large-grant project on the epidemiology of bovine tuberculosis in wild badgers, using state-of-the-art Bayesian modelling approaches to study the drivers of infectiousness and transmission of infection in