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funded by UKRI EPSRC and is fixed term for 12 months. You will be contributing to joint UKRI EPSRC – NSF CBET project on sustainable computer networks, with a focus on carbon emissions reduction and
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attached to the project. The successful applicant must hold a PhD/DPhil in a relevant subject. They must have peer-reviewed publications using data science approaches, for example, genetic analysis
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Applications are invited for a Postdoctoral Research Assistant in Data processing for the MIGHTEE survey. This is a senior role funded through the UKRI Frontier Research Grant of Prof. Matthew
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Postdoctoral Researcher Data Scientist. You will play an important role in the contribution of statistical analysis and new models of analysis of complex data sets. You will be responsible for providing analysis
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independent study and training courses. It is essential that you hold a PhD/DPhil (or close to completion) in mathematics, statistics, physics, engineering, data science or a related discipline, and have
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projects in computer vision research, with a particular emphasis on Spatial Intelligence, 3D Computer Vision, and 3D Generative AI. You should hold a relevant PhD/DPhil (or near completion*) in Computer
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applicant must hold a PhD/DPhil in a relevant subject. They must have peer-reviewed publications using data science approaches, for example, genetic analysis, including Mendelian randomisation and genetic co
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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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on modelling of the transport, electrochemistry, and mechanics of next-generation lithium/air electrode materials and cell architectures. Using input data from experiments, the post holder will develop and
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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