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Monitoring provides us with vital insights about how we use rivers and our impacts on them. They are also crucial tools in river governance, providing policy-makers and regulators with evidence to
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. This involves 'handcrafted' expert systems, which are good at reasoning about narrowly defined problems, but poor at handling uncertainty and have no ability to learn or abstract/generalise. In that sense
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process configurations. In practice, this might not be possible, that is the sample data could cover only some space, not entire space, of process parameters. Integrating prior knowledge into the learning
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image correlation is an effective tool to characterize material properties. The analysis of the images can provide a fair assessment about the changes in material behaviour under different operational
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. The student will have the opportunity to work with experts in the data analytics and condition monitoring field, as well as being part of our strong and dynamic research centre at Cranfield University. About
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communication skills for regular interaction with other stakeholders, with an interest for industrial research. Funding This is a self-funded research opportunity. Find out more about tuition fees. Cranfield