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challenge. We seek a senior computational biologist to apply these extensive in-house datasets toward the development of novel, domain-tailored machine-learning models and analytical methods. You will explore
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. The Department seeks candidates with interests in Statistical research at the interface of machine learning and AI. They will have the skills and enthusiasm to lecture graduate level, over a wide range of topics
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, learning and decision making, you will have strong quantitative and programming skills along with a track record of designing neuromodulation and neuroimaging studies in healthy participants, of using
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highly computer literate, with demonstrable experience in using common software applications e.g. MS Word, Excel, Outlook, Adobe Acrobat, and have the ability to learn quickly and use specialist software
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discipline (eg Statistics, Machine Learning, Biostatistics, AI, Engineering) with experience of developing and applying new methods. You will be able to develop research projects, with publications in peer
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-qualification research experience. Relevant areas of research include computational chemistry, structural biology/bioinformatics, statistics, machine learning, computer science or mathematics. They will have a
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, distance learning MSc in Integrated Immunology. The course launched in the 2024-25 academic year, and is closely linked to our well-established full-time MSc in Integrated Immunology based in Oxford. This is
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). This role will primarily support the Royal Academy of Engineering Chair of Clinical Machine Learning, Professor David Clifton, as well as other academic members of the group. The position is permanent and
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would be desirable to have knowledge and experience of applied artificial intelligence/machine learning and a chartered Statistician (CStat) qualification. This role is advertised at a grade 8; however
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of the Institute is to improve tools in, and knowledge from, genetics, genomics, molecular and single cell biology, spatial imaging, machine learning and novel methods of data handling to study the pattern