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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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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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. 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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collaborators. The post is currently available for a start date as soon as possible from 1st July 2025, but later start dates can be negotiated. You will have a PhD in Astrophysics, Applied Mathematics, or a
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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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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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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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positive impact through cross-disciplinary interactions. Actively seeking new funding and creating opportunity for spinouts. Working towards real-world outcomes. Integrating large-scale data, AI, and
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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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will possess a relevant PhD or equivalent qualification/experience in a relevant field of study (e.g. data science, AI, machine learning, statistics, physics). They will be motivated to solve problems