163 phd-data-mining Postdoctoral research jobs at University of Oxford in United Kingdom
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use computational approaches to mine natural biodiversity in gene sequences to identify engineering targets to increase lipid content and enhance the water use efficiency. The project will make use
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human tumour models including organ/tumour perfusion, slice culture and organoids to ensure data is clinically relevant and to inspire the next generation of effective treatments. The post would suit
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developing new optogenetic treatments for inherited retinal diseases. We are looking for highly qualified individual (PhD/DPhil) with outstanding academic credentials, who can work well under pressure and
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blotting, microscopy, and drug/compound co-treatment in cellular assays Experience in antibiotic drug discovery You must also: Hold a PhD/DPhil in medicinal chemistry and chemical biology, together
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
, epidemiology, and socio-environmental modelling. To be considered a successful candidate; A PhD degree in Ecology, Biodiversity analyses, Environmental Science, Remote Sensing, Epidemiology, Data Science, or a
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interpretation of atmospheric circulation in high-resolution reanalysis data, idealised model simulations and a state-of-the-art weather forecasting system. The post-holder will have the opportunity to teach
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DPhil students, manage data analysis pipelines, and contribute to publications and grant writing. This post is ideally suited to someone aiming to secure a long-term fellowship and build an independent
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on qualifications and relevant skills acquired and will also be determined by the funding available. About you You should hold a PhD/DPhil, or be close to completion, of a relevant PhD/DPhil with a proven record of
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the application of health economics methods to patient-level data as well as acting as a source of information and advice to other members of the group on health economic methodologies or procedures. About You You
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, including molecular clouds (properties, formation, evolution), dynamics (supermassive black hole mass measurements, gas flows, active galactic nucleus feedback), and any other facets of the data not yet