14 linked-data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" Postdoctoral positions at Queen Mary University of London
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males and females respond differently to bacterial infection. The successful candidate will play a leading role in the imaging and data analysis components of the project. They will develop and apply high
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linking intermittent hypoxia to cardiovascular dysfunction in obstructive sleep apnoea (OSA), a common clinical condition associated with cardiovascular risk. The project combines in vivo cardiovascular
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, or be close to completing, a PhD in statistical genomics, genetic epidemiology, data science, computing, artificial intelligence, biomedical engineering, or a related field. You will have significant
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the John Templeton Foundation. Gravity from Entropy is a statistical mechanics approach that derives gravity from principles of information theory and differential geometry. The aim of the project is to
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learning for cardiovascular digital twins and AI-enabled precision treatment. The postholder will develop patient-specific models that integrate multimodal clinical, physiological, imaging and sensor data
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closely with Dr James Nicholson and collaborators, analyse and interpret data, supervise students, and disseminate findings through first-author publications and conference presentations. This 42-month
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field. The successful candidate must possess expertise in distributed AI/ML systems and computer networks. Good knowledge and practical skills in distributed AI/ML, networked systems, data management, and
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, collaborating closely with a similar post-holder in Wales. In the first year, this will involve developing information materials to support the offer to choice, collaborating closely with the NHS and patient and
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-disciplinary research in digital and data science, including artificial intelligence (AI). The role is jointly split with the Cardiovascular Devices Hub which brings together clinicians, academics, engineers and
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, computational biology, genomics, or a related quantitative field. You will have strong programming skills (Python, R, Linux) and experience analysing large-scale sequencing datasets, ideally RNA-sequencing data