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Contribute to the creation of a large database on historical banknote users Collect and summarise relevant background information about monetary and financial history in modern Britain between 1690s and 1920s
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to data analysis and biological interpretation. Role Summary Develop, implement, and apply advanced reproducible computational tools and workflows to process, analyse, and interpret large-scale LC–MS-based
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observation tasks, health economics data and a large battery of questionnaires. Because of the quality of the datasets, the elevated risk of children involved and the importance of the research questions, we
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teaching activities. You hold a PhD in microbiology/microbial ecology or similar, and you have experience in bioinformatic methods for analyzing environmental sequencing data (metagenomes, amplicons, long
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turbulence data, together with fine-scale profiles from standard Argo floats, to quantify rates of vertical and horizontal ocean mixing, and you will apply inverse methods to investigate the role
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will develop, implement, and apply advanced computational tools and reproducible workflows to interrogate large-scale, liquid chromatography–mass spectrometry (LC–MS)-based comparative metabolomics
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data and a large battery of questionnaires. Because of the quality of the datasets, the elevated risk of children involved and the importance of the research questions, we anticipate submission of a
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current and emerging trends in data science. Committee Membership: Participate in the DFM research committee. Qualifications Educational Background: Master’s or PhD in Data Science or a related field
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collaborative platform to: (i) establish standards and protocols for comparative methods; (ii) assemble and coordinate a team of international researchers; and (iii) enable open sharing of data, evidence, and
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: interoceptive mechanisms of anxiety after cancer’. The award is supporting a large-scale collaborative research programme between KCL, UCL, Stanford University, and the National Cancer Institute (NIH) through