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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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Fellow will be using Natural 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
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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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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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turbulence data, together with fine-scale profiles from standard Argo floats, to quantify rates of vertical and horizontal ocean mixing, and you will apply inverse methods to investigate the role
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’) with responsibility for the day-to-day project, budget and research activities. You will also undertake research including developing and fine-tuning large language models and topic modelling methods
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About Us PharosAI offers a unique cancer AI product development ecosystem for drug discovery and clinical applications, democratising access to data, AI models, technologies, and capabilities
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properties of vibrational sources in large built-up structures, such as cars or airplanes. We will incorporate data from measurements and implement these sources into large-scale structure-borne sound
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the presence of significant confounding factors Organise large-scale sequence data sets Communicate results at project meetings and conferences Present research outputs, including drafting academic publications
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About Us PharosAI offers a unique cancer AI product development ecosystem for drug discovery and clinical applications, democratising access to data, AI models, technologies, and capabilities