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School of Computing & Mathematical Sciences Location: Greenwich and Medway Campuses Salary: £38,249 to £44,128 Contract Type: Permanent Release Date: Friday 25 July 2025 Closing Date: Friday 08 August 2025 Interview Date: To be confirmed Reference: FES015-E We invite applications outlining...
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The University of Bristol is seeking a Research Associate to work with Dr Ben Faber on a Wellcome Trust-funded project entitled ‘Utilising large joint structural phenotypes of osteoarthritis
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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(or equivalent) in a biomedical science. Experience in neuroscience and/or immunology is desirable. Project key words Retinal imaging, data-analytics, computer vision, big data Funding The studentship, funded by
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, analysing data and presenting research findings in various settings, under the support and direction of the supervisory team. You will work with big data including bioinformatic data and epidemiological data
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including designing and conducting experiments, analysing data and presenting research findings in various settings, under the support and direction of the supervisory team. You will work with big data
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models, working with Geographic Information Systems, handling large geographical datasets, statistically analysing (geospatial) data, and intensely collaborating with researchers from different disciplines
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artificial intelligence methodologies. The successful candidate will work at the forefront of computational biology, developing novel approaches for large-scale genomic data analysis and contributing
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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