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established and emerging bioinformatics, statistical modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics
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publications prior to the panel interview. In addition to further excelling your skills in Computer Vision/Big Data/Machine Learning analyses, this opportunity enables you to: - Work closely with clinicians
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of Dentistry, Oral & Craniofacial Sciences at King's College London. Our methodological work spans trustworthy AI, multimodal machine learning and statistical signal processing. Our translational work applies
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of an extension, subject to funding. You will apply and develop cutting-edge machine learning methods to integrate and analyse multi-omic data to identify disease phenotypes. A key aspect of the role is to bridge
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), with a start date from the 01st January 2027. You should hold a PhD in Computer Science, with expertise in Natural Language Processing, and have a demonstrated track record of research
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, Statistics, Computer Science or conjugate subject and have a strong record of publication in the relevant literature. Good knowledge of machine learning algorithms is essential, as well as proven competence in
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-scale, diverse datasets using machine learning and AI techniques. Findings will be disseminated through peer-reviewed publications, conference presentations, and public engagement. About You You will hold
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). The researcher should have a PhD/DPhil in robotics, computer vision, machine learning or a closely related field. You have an excellent academic track record in topics relevant to robot perception. A specific
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modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics, and metabolomics. Working closely with senior
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computational and machine learning approaches. What We Offer As an employer, we genuinely care about our employees’ wellbeing and this is reflected in the range of benefits that we offer including