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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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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
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Physics was top in the UK for world-leading research outputs. Our joint submission to Engineering with the University of Edinburgh was ranked 1st in Scotland and 3rd in the UK for quality and breadth
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scalable models aligned with current and future needs. This project addresses infrastructure challenges and contributes to the UK's construction industry by leveraging LLMs. Project Background: The UK's
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Systems is four-year programme offered by the universities of Edinburgh, Glasgow, Heriot-Watt and Strathclyde. These longer-term research partnerships are designed to allow participating companies to drive