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remains challenging, particularly for patients with vague or non-specific symptoms. Electronic health records provide unprecedented opportunities to develop personalised cancer risk prediction models, but
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of Chichester are pleased to announce the availability of a fully funded Collaborative doctoral studentship from October 2026 under the AHRC’s https://www.ahrc-cdp.org/2025-ahrc-collaborative-doctoral
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biostatistics. We develop, apply and promote innovative statistical and data science approaches to advance biomedical science and human health. The BSU current research portfolio is organised into five main
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signals is hard. Real-world data is noisy, assumptions don't always hold, and the stakes of getting it wrong are high. You'll use and help further develop an open-source Julia-based toolkit, developed by co
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D'Souza ([email protected] ). Please read the description below in full before directly contacting us by email. Your role and goals You will develop data-driven and machine learning workflows to predict
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to announce the availability of a fully funded Collaborative doctoral studentship from October 2026 under the AHRC’s https://www.ahrc-cdp.org/2025-ahrc-collaborative-doctoral-partnership-studentships
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markets, yet credible evidence on its long-term economic impact remains limited by the absence of robust measures of AI adoption, diffusion, and labour market adjustment. This PhD project will develop new
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) Industrial partner: BAE Systems plc Academic supervisor: Dr Sendy Phang, Dr. George Gordon and Dr Alexander Turner Industry supervisor: Dr Hassan Zaidi We are seeking a Ph.D. student to develop next-generation
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to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show