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Language Processing (NLP) methods, with a special focus on generative Large Language Models (LLMs), to interrogate a very large sample of Electronic Health Records from people with epilepsy across multiple NHS
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generative Large Language Models (LLMs), to interrogate a very large sample of Electronic Health Records from people with epilepsy across multiple NHS hospitals. They are expected to have some experience
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very good working knowledge of statistically packages such as SPSS, AMOS, Stata or R Experience of cleaning, recoding and cataloguing large and complex data sets suitable for time-dependent
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. This role represents a unique opportunity to generate biological insights from our large-scale research datasets including single-cell multiomic sequencing data from skin and blood to enable
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for implementing the model as a computer simulation and analysing it within a health-economics framework using standard computational techniques. The post-holder will also be responsible for writing up the findings
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that the structural models use high-fidelity aerodynamic data to compute the aerodynamic loads and inform the overall system design. About You You will hold a PhD (or close to completion) in aerospace engineering
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graduates on challenging, high-profile projects. Further information is available at: www.birmingham.ac.uk/ktp Role Summary The post holder will carry out research on and work with Salinity's customers
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and interpreting research findings and results based on large scale media data sets Contributing to engagement with non-academic partners, co-produce new knowledge, contribute to public understanding
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Translational Centre. Plan and publish high quality research, supported in this by the Centre Leads and Deputy leads. Conduct secondary data analyses. Expertise in big data would be valuable as well as advanced