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Project title: Biometric deepfake to physical attack instrument assessment Supervisory Team: Richard Guest and Jennifer Williams Project description: Deepfake technologies have increased
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range of opportunities to enhance your professional development and transferable skills. The Faculty of Engineering and Physical Sciences covers diverse topics in the areas of Chemistry and Chemical
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is still not a comprehensive understanding of the discriminator's contributions. Similarly, the role of the physics-informed loss function to improve the predictive capability is largely unknown
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to set reduction targets and implement corresponding reduction measures. Reliable and accurate in-silico predictions to identify sustainable process opportunities including resource efficiency, pollution
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, the process of recovering real-space images remains unclear due to the inherent and currently intractable complexity of deep learning methods. In this project you will develop Physics-Aware Super-Resolution
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This project could be right for you if you enjoy solid mechanics and structures, have an inclination toward computational and analytical mechanics, and are also interested in carrying out physical experiments
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Apply online, by clicking the 'Apply' button, above. Select programme type (Research), 2024/25, Faculty of Engineering and Physical Sciences, next page select “PhD Engineering & Environment (Full time
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' button, above. Select programme type (Research), 2024/25, Faculty of Physical Sciences and Engineering, next page select “PhD CDT CISDnS (Full time)”. In Section 2 of the application form you should insert
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online, by clicking the 'Apply' button, above. Select programme type (Research), 2024/25, Faculty of Engineering and Physical Sciences, next page select “PhD Engineering & Environment (Full time)”. In
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suitable for applicants with a high level degree in Physics, Chemistry or Materials Science, ideally with some prior experience in quantum chemistry or solid state electronic structure calculations