323 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" positions at University of Sheffield in United Kingdom
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health to line managers and other internal stakeholders. Assist to develop and evaluate processes for gathering, analysing, interpreting, and presenting data to support continued improvement of the OH
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experience/expertise in transfer learning for SHM data; preferably, kernel-based, neural network and Bayesian. Essential Interview Experience and track record in code writing for engineering problems in e.g
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data collection, analysis and storage on a day-to-day basis. Work independently and as part of a team to deliver the research objectives in line with the project outline. Direct the work of supporting
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PhD in a relevant subject area Desirable Application/interview Further Information Grade 8 Salary £48,822 - £53,301 per annum Work arrangement Full-time (part-time/job-share applications are welcome
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engineers, healthcare researchers, health data experts and health service providers. It seeks to integrate the human (ensuring person-centred preferences about care) with the technological ( “digital twin
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for more information about the lab: https://sites.google.com/sheffield.ac.uk/sheffieldcogdev/home Funding Notes Self funded or externally sponsored students only. Intakes are usually October and March
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in spatial-analysis, optimisation and economic analysis, as well as contribute to the UK’s hydrogen economy. How to Apply: Please see this link for information on how to apply: https
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: Please see this link for information on how to apply: https://www.sheffield.ac.uk/cbe/postgraduate/phd/how-apply. Please include the name of your proposed supervisor and the title of the PhD project within
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receive information, but will perform complex machine learning (AI) and processing tasks. This "Edge Computing" reduces latency, improves security and reliability, and makes complex multi-node systems
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simulation. A successful candidate will join a well-funded and highly active research group with a worldwide reputation for excellence (https://ldsd.group.shef.ac.uk/research/polaritons/). The group possesses