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profound interest in inorganic chemistry, in both experimental and modelling applications. We are looking for candidates who are also interested in the analytical and numerical aspects of the work to support
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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
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with a surface. This project will involve using and further developing both the experimental and data analysis methods that are currently used within the research team. The student will learn how to use
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this astonishing picometre fabrication precision. Further aims of the project include: Theoretical modelling of nanoscale effects and processes in SNAP Development of experimental methods of picometre-precise
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in a degree, ideally at Masters level, in an Engineering subject, Physics, Mathematics, Computer Science or other quantitative background. Knowledge in fluid mechanics, ocean waves, numerical methods
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sensitive to malicious deviations while remaining resource efficient. Solutions must operate effectively on network gateways or even capable IoT devices. The research will investigate statistical methods
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, ultimately optimising the deposition process. Additive manufacturing (AM) is a rapidly advancing technology, driving numerous innovations and finding diverse applications across industries such as aerospace
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Involvement in the preparation of articles for publication in scientific journal(s) Good numerical and statistics skills and familiarity with text editing software, such as Word, Excel, etc. Knowledge
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experimental methods to improve them, alongside developing new approaches to enhance these properties. External environmental factors, such as humidity, pressure, and temperature, will also be key variables
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alongside numerical simulations relying on high-performance computing and reduced order modelling. We aim to gain new insights about the physical coherent structures which are most relevant to viscoelastic