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statistical and computational methods designed to use “big data” and to address questions of direct or indirect relevance to common complex diseases and disorders. The appointee will join the group of Professor
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research environment supported by a team with broad expertise in data science, infectious diseases, hepatology, and clinical informatics. You will take a leading role in analysing large-scale, longitudinal
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statistical and computational methods designed to use “big data” and to address questions of direct or indirect relevance to common complex diseases and disorders. The appointee will join the group of Professor
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related field together with strong programming skills in Python, R, or similar languages, and proficiency in high-performance computing. You will have experience in large-scale genomic data analysis. You
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will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and help supervise associated PhD students. The successful candidates will join large, supportive
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R or equivalent skills in another relevant language. We are not expecting you to be an expert in all forms of computer simulation, Large Language Models, or machine learning etc, but a working
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at command line and BASH scripting Experience working with large scale, complex datasets and data wrangling skills Strong publication record and familiarity with the existing literature and research in
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at command line and BASH scripting Experience working with large scale, complex datasets and data wrangling skills Strong publication record and familiarity with the existing literature and research in
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amenable to therapeutic targeting. This position will involve the application of advanced data science approaches to explore large-scale clinical datasets extracted from electronic health records, with
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to the 4th February 2026. You will be investigating the safety and security implications of large language model (LLM) agents, particularly those capable of interacting with operating systems and external APIs