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landscape, from SMEs and start-ups to OEMs and large-scale global manufacturers. For more information please visit the MTC website . Contact For further information on this PhD position please contact Dr
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connectivity seen in large scale brain recordings. These describe correlations between brain regions and can evolve over tens of seconds, with essentially discontinuous shifts from one short term state
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distribution. This process often takes place in large scale driers where the material is heated and broken up mechanically with mixing blades. However, under certain conditions the process can break down as the
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advanced simulation methods, including Reynolds-Averaged Navier-Stokes (RANS), Direct Numerical Simulations (DNS), and/or Large Eddy Simulations (LES), will be employed to accurately model the complex flow
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coefficients. This strategy carries large uncertainty and requires vast amount of expensive and time-consuming experimental data. Worse, sometimes the experimental data is simply inaccessible. The need for cost
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methods in the past. A piece of comprehensive computer software, Pythia with the corresponding capabilities have been developed and tested successfully in several industrial applications. The software can
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. This primarily stems from the challenging materials (large/disordered unit-cells, long sampling timescales) and light-matter interactions involved. Consequently, computational tools, rooted in physics, that can
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Project title: Privacy/Security Risks in Machine/Federated Learning systems Supervisory Team: Dr Han Wu Project description: In the wake of growing data privacy concerns and the enactment
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algorithms are used that allow a computer to process large data-sets and learn patterns and behaviours, thus allowing them to respond when the same patterns are seen in new data. This include 'supervised