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Field
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One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour
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the coupled effect on supersonic combustion. This data can then help support future design efforts, which requires validation data where the effects of thermal warpage can be included. To achieve
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to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show
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nutrition and exercise trials Excellent oral and written communication skills Ability to critically appraise scientific methodology and data Ability to work well individually and as a member of a larger
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such as landslide movement style, runout, and how landslide hazards evolve over time. This Ph.D. project will leverage the analysis of new time-series data from cloud-based satellite image archives
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features enhance binding to the receptors. This information will be carried forward to human tasting panels. You will also investigate how other components of food matrices inhibit binding. You will thus
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developed by University Hospital Sussex in collaboration with their industrial partner, and which makes it possible to collect data from both layers of the heart at the same time. Key aims of this project
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will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show challenging properties of uncertainty, irregularity and
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/developing-people-and-skills/stfc/training/studentship-information-for-students/payments-to-students/ ). An additional Research training support grant totalling £5,000 is available for the duration
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Assistants is £32,546 - £35,116 and for Research Associates this is £37,174 - £45,413 per annum. Suitable candidates should have previous experience of genetic analysis of large scale genome sequence data and