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by anxiety, depression, eating disorders and other mental health conditions. About the role: We are seeking a highly motivated postdoctoral Research Fellow in statistical genetics and genomic data
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conduct of in-home, telephone, and online qualitative interviews. The role will also involve making a substantial contribution to qualitative data management and analysis. You will be part of a vibrant and
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of healthy aging using cutting-edge single-cell and AI-based tools, and population cohort data. You will be an integral member of the Awadalla lab, working with some of the world’s largest single-cell data
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Researcher to explore the cellular and genomic determinants of healthy aging using cutting-edge single-cell and AI-based tools, and population cohort data. You will be an integral member of the Awadalla lab
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) to provide benchmark data as well as the quantum technology gravity gradient sensor. This involves close liaison with colleagues across campus, especially as part of QuSIT, partner institutions, project
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the 1970-2010 average. The role will involve undertaking plant taphonomy experiments and generating chemical data from experimental and fossils plants to compare with morphological and anatomical traits and
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The postdoctoral researcher will lead the development of computational methods for aligning cortical organisation across species using transcriptomic and anatomical data combined with modern machine
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-to-phenotype models for human health at the Big Data Institute (BDI), University of Oxford. The successful candidate will contribute to a strategic research programme integrating population-scale biomedical data
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reproducibility of biological assays, nucleic acid sequencing and analysis. You will hold an undergraduate degree in biomedical sciences with a working knowledge of data analysis including statistical analysis
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conditions. The researcher will also work with team members within the consortium in generating necessary data required for developing a machine learning model for storm surge prediction. Key Responsibilities