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of Glasgow/Ifakara Health Institute) to develop and test new methods for trial design and analysis. Developing statistical models and code to run the proposed methods. Developing and running simulation-based
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modellers using advanced simulations to interpret and validate observations via data assimilation. There will be opportunities to spend time with project partners at UCLA (Prof. James McWilliams) and attend
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in statistics, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded
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with epilepsy across multiple NHS hospitals. They are expected to have some experience working with NLP in general and LLMs in particular. They will also help to further develop machine learning models
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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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, the development and fine-tuning of vision foundation models, multiple instance learning, survival analysis, and interpretable model development. You will also lead efforts in building multimodal deep learning
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, the development and fine-tuning of vision foundation models, multiple instance learning, survival analysis, and interpretable model development. You will also lead efforts in building multimodal deep learning
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the Medical Research Council. The Research 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
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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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the Medical Research Council. The Research 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