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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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of admission for the PhD programme for September 2023 entry can be considered for this studentship. Contact details for enquiries Useful links Back to list of opportunities
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integrates design, technology and management expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base of manufacturing research
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development. Interested? Apply Now! For more information, please contact Prof. Rob Dwyer-Joyce at r.dwyer-joyce@sheffield.ac.uk. Ready to take the next step? Visit PhD study | MAC | The University of Sheffield
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this to data from X-ray satellites and attempt to constrain misalignment directly. The student will also have the opportunity to explore new GR-RMHD simulations which are being carried out by Prof Middleton’s
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of dehydration using a low-power radio-frequency (RF) sensor. The research objectives include design optimization to improve wearability, robust data acquisition using machine learning and establishing correlation
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, embrittlement, and cracks. This will be achieved by integrating ultrasonic arrays with inverse modelling methods to interpret historical data. Additionally, the project will explore the failure mechanisms
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instrumentation for acoustic flow measurements, sensitivity to intake operating conditions and the exploration of data analysis methods to improve the overall measurement system accuracy. It will also include
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opportunity! For more information, please contact Prof. Rob Dwyer-Joyce at r.dwyer-joyce@sheffield.ac.uk Learn More: Leonardo Centre: www.sheffield.ac.uk/leonardocentre John Crane Ltd: www.johncrane.com Become
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catalytic process. In addition, it is important to improve the student the experimental skill, materials characterization skill and data analysis skill. Student who joins our group will learn the fundamentals