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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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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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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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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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& Computer Science, University of Southampton. Before joining Southampton, he was a Postdoc at the UCL Electronic & Electrical Engineering. He has extensive experience in design and fabrication of novel designs in low
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for All). Dr Sam Fawkner (University of Edinburgh) and Prof Trish Gorely (University of the Highlands and Islands) are the supporting academics for the project. In line with Paths for All’s mission
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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