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use this formalisation to encode our STV algorithm on encrypted ballots. This approach aims to ensure both the correctness and privacy of the tallying process, paving the way for verifiable and secure
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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-based structural integrity model, validated using synchrotron X-ray microtomography and phase contrast imaging, to predict the lifetime of UK’s advanced gas-cooled reactors fuel cladding in storage
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the interpretability of these models can be enhanced to support clinical decision-making. This project will leverage the complementary expertise of both supervisory teams in EEG signal processing, graph deep learning
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, combustion, and process optimisation. The project is focussed on the development of novel interface capturing Computational Fluid Dynamics methods for simulating boiling in Nuclear Thermal Hydraulics
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—quality post-graduate research development and training environment of the University of Nottingham. This PhD scholarship is offered in collaboration with the UKRI funded transdisciplinary hub
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—quality post-graduate research development and training environment of the University of Nottingham. This PhD scholarship is offered in collaboration with the UKRI funded transdisciplinary hub
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the foundation for the development of a 'space-based early warning system' of a swarm of micro satellites each to individually tag asteroids that could hit the Earth. The post will provide an excellent opportunity
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Award (IDLA). This research aims to investigate natural source zone depletion (NSZD) processes that can naturally remedy oil pollution and use this improved process understanding to enhance CoronaScreen
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sustainable aviation fuel (SAF), and importantly, hydrogen. Plastics are comprised of numerous polymers, thus the products of each vary through chemical recycling processes This project seeks to develop an in