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cutting-edge image-based multiphysics modelling of cardiovascular fluid dynamics and device-tissue interactions. You will work with clinical and experimental data to develop innovative geometric deep
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are experts in cutting-edge image-based multiphysics modelling of cardiovascular fluid dynamics and device-tissue interactions. You will work with clinical and experimental data to develop innovative geometric
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this role, you will work as part of the world-class team of researchers and software developers within the PSS team to develop all or some of firmware, software and algorithms for pulsar and fast transient
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project team regularly use for the production of model colloidal films, ceramic dielectrics, photovoltaics and battery electrodes to provide the datasets required to educate the machine learning algorithms
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. The task of the theory group led by Prof Kyriienko at the University of Sheffield within the consortium is to lead nationally the development of quantum machine learning (QML) algorithms. The research will
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to test the current algorithm and inform development of future algorithm refinements aimed at supporting diabetic foot ulcer (DFU) prevention through identification of temperature differences of > 2.2°C
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at Sheffield by Prof. John Derrick and Dr. Andrei Popescu and sponsored by the Engineering and Physical Sciences Research Council (EPSRC). The project aims to conduct research into the safety and security
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. They will also contribute to outreach activities and be proactive in student recruitment activities. In addition, the successful candidate will contribute to research, enterprise development and knowledge
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. By integrating cutting-edge multi-agent systems, federated learning, and game theory, this project will develop sophisticated decentralised algorithms that enable autonomous vehicles (AVs
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work with researchers on the DASS programme to develop and promote freely available software, implementing new statistical methods and algorithms for identifying anomalous structure in stream settings