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information and other funding options: View Website Eligibility Students are expected to hold a 2.1 Hons degree or above, or equivalent, in Electronics and Electrical Engineering, Computer Science, Physics
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technology. Our ambition is to push the frontiers of electronics through emerging technologies, disrupting current ways of thinking by innovating advanced nano/biosensors, safe and efficient energy storage
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EPCC at the University of Edinburgh is the UK’s leading centre for Supercomputing and Data Analytics. We are seeking a Data Architect to work as technical lead in maximising the capabilities
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for this project would have first degree and MSc/MEng in physics, electronic and electrical engineering or a related discipline. A passion for experimental work and capability to develop/apply mathematical modelling
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learning approaches for biological design, and the PDRA will work closely with data scientists at the University of Edinburgh to build predictive models that can accelerate the design of genetic circuits in
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for machine learning approaches for biological design, and the PDRA will work closely with data scientists at the University of Edinburgh to build predictive models that can accelerate the design of genetic
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matching that of current oil and gas infrastructure (Krevor et al., 2023). The use of CCS in these models is the leading control on the total costs of mitigating climate change. However, these models
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Principal Supervisor: Dr Khushboo Pandey Eligibility: The candidate should have a master’s degree in either Physics or Engineering. Minimum entry qualification - an Honours degree at 2:1 or above
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, cavitation is a major problem in engineering, as high-speed jets can develop during their collapse upon contact with solids, which are responsible for pitting wear, and even full structural failure
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and reliability in the clean energy sector. Outputs from this project will influence real world technology, leading to industry scale testing with one of the global leaders in wind energy. The position