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and machine learning techniques for the design of superconducting qubits, one of the leading qubit modalities used in today’s quantum computers. The optimal design of superconducting qubits is a highly
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PhD researcher will contribute to developing responsible, efficient, and trustworthy AI systems from cognitive fatigue management and personalised thermal comfort to multi modal medical imaging and IoT
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Apply and key information This project is funded by: Department for the Economy (DfE) Summary There is both growing anxiety and optimism around the use of Artificial Intelligence (AI) in
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monitoring system will support control of welding parameters and help optimize robot tool paths. The aim is to achieve a right-first-time approach, with additional benefits of reducing energy and material
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to the understanding that an integrated, multi-omics analysis may be optimal for unravelling this disease. This PhD studentship will focus on the development of data driven clinical data analysis through integration
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, climate control, and irrigation systems, poses critical challenges to its economic viability and environmental sustainability. This PhD project aims to design, develop, and optimise a climate-smart, net
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process modifications post treatment. To leverage the data from ‘2’ above to monitor the effects of modifying therapy parameters with a view towards therapy optimization. Important Information: Applications
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eligible to apply for an award. Due consideration should be given to financing your studies . *Part time PhD scholarships may be available, based on 0.5 of the full time rate, and will require a six year
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an optimized solution with renewable energy (RE) implementation for power generation to replace fossil fuels. The effects of reducing greenhouse gases through the implementation of renewable energy sources
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Summary Meeting future energy demands requires efficient, low-carbon systems capable of storing and releasing heat when needed. This PhD project aims to develop next-generation latent heat thermal