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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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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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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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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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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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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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to impact medical treatments and technology advancements, this project promises an exciting and important avenue for personalized medicine. The project will collaborate with a multi-disciplinary team
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and budgets. Procurement at the University of Edinburgh has undergone a major transformation as we extend the scope of our influence and impact across our £1bn world-renowned organisation and introduce
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London, United Kingdom. The researcher will be supervised jointly by Dr. Yali Du (University of Edinburgh) and Dr. Biwei Huang (University of California San Diego). The candidate will be a conscientious