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training in computational tools and statistical methods over the course of the project. The project includes placements at NPL and Waters-TA Instruments, with opportunities to work in state-of-the-art
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-economics. Experience in working with datasets and prior coursework in probability theory and statistics will be helpful, but not necessary to apply for the position. How to apply: Please choose Electrical
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analyse large datasets such as the Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics to identify activity related to the treatment of community acquired pneumonia. This will require
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datasets, therefore, there will be a focus in the implementation of models for large volumes of data. The project will work in an exciting interface of statistics and machine learning and has the potential
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the context of computing Familiarity with research tools and methods, including statistics platforms like R and/or thematic analysis Knowledge of user-centred design and research methods involving human
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quantitative analysis skills and experience developing algorithms and/or conducting statistical analyses with biological datasets. Background and work knowledge in statistics, algorithms, optimization of novel
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, including: Genomic technologies – hands-on experience in long-read sequencing and variant interpretation Bioinformatics – pipeline development, visualisation, and statistical modelling PRS – applying big data
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an early warning system of dementia, to be exploited within existing healthcare pathways to trigger early intervention. Skills acquisition The studentship will provide training in data-analytics, statistics
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sensitive to malicious deviations while remaining resource efficient. Solutions must operate effectively on network gateways or even capable IoT devices. The research will investigate statistical methods
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specific details under the 'Prob_AI' heading: PhD Projects | School of Mathematics The Prob_AI Hub aims to bring together researchers in Applied Mathematics, Probability, and Statistics to tackle challenges