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and machine learning algorithms to deliver quantitative diagnosis without destroying the samples. The AF-Raman prototype will be integrated and tested in the operating theatre at the Nottingham Breast
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during pandemics. Populating these instances with real-world data we would then develop novel algorithms to solve them. The selected candidate would disseminate their research by publishing in top-tiered
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research in the field of AI for healthcare autonomous systems. Activities on non-healthcare systems could occasionally be requested. • Undertake research from algorithm development to real time
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of classification algorithms Correlate/Integrate In Vivo and Ex Vivo metabolite analysis to understand the key metabolic pathways in different tumour types and subtypes Identify and harmonise MRI and MRS acquisition
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uses, improving the AI and MRI algorithms, and linking them with information from biological studies on tumour tissue. This project harnesses AI to improve diagnosis and clinical decision-making leading
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research in the field of AI for healthcare autonomous systems. Activities on non-healthcare systems could occasionally be requested. • Undertake research from algorithm development to real time
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. There are opportunities to broaden out into other areas such as new algorithm development, and advanced computational methodologies for integrated analyses. You will have a key role in planning, designing and executing a
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Desirable criteria Experience of advanced statistical and/or machine learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial
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learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial analysis Strong publication record Experience in women and children’s
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systems beyond commercially available peptide based systems. A6 Knowledge of data science driven approaches to drug discovery algorithms. For appointment at Grade 8: A4 Some reputation in, and insight