120 structural-engineering-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dip" positions at King's College London in United Kingdom
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) is a vibrant faculty based in the heart of London with a long tradition of world-leading research and teaching in physics
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structures, interventions and outcome measures across the research areas of the Faculty. NMPC researchers collaborate in applications for trials of complex interventions, adaptive designs, cluster randomised
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Faculty structure Downloading a copy of our Job Description Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) is a vibrant faculty based in the heart of London with a long tradition of world-leading research and teaching in physics
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leading innovation at the interface of AI and disciplines such as Health, Technology, Security, Creative Industries, Business, Law and Education. The professors will serve as matter-expert champions
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scientific concepts. 4. Excellent writing skills, with demonstrable experience of delivering clear, structured outputs that deliver results. Excellent qualitative and quantitative analytical and problem
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Kuberan Pushparajah and Dr Alessandra Frigiola within the Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Sciences, King’s College London. About the role Applications
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based in the School of Biomedical Engineering & Imaging Sciences , and specifically within the MRI Clinical Research Department located in St Thomas’ Hospital. The School of Biomedical Engineering
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. Knowledge of best practice process improvement and the capability to leverage available technology, data and reporting to improve new and existing processes. Experience of how to successfully roll out new
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following skills and experience: Essential criteria PhD in applied mathematics, statistics, engineering, computational biology, econometrics, or a related discipline. Experience in developing complex models