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workshops.The PhD students will focus on using state-of-the-art computational and statistical techniques to shed light on the fundamental mechanisms of decision-making.We are particularly interested in candidates
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, psychology, health economics, statistics, health services research), and with a commitment to conducting excellent and innovative research that will advance care, support and outcomes. Example topic areas
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appropriate statistical testing to test the efficacy of the models. The project forms part of a wider effort for developing an effective VR HRI toolkit for improving interactive fluidity between robots and
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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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economic studies funded by the UK National Institute for Health and Care Research. Experience of conducting economic evaluations using suitable statistical software (e.g. STATA, R or SAS) is essential
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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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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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, 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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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