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under real-world conditions to verify system operation against targets and demonstrate the reliability of the technology for use in backup power, grid stabilisation, and renewable energy integration
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are provided in Arts and Humanities, Built Environment, Brain Sciences, Engineering Sciences, Education, Laws, Life Sciences, Mathematical & Physical Sciences, Medical Sciences, Population Health Sciences and
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their application clearly which they are familiar with and their degree of expertise). Experience of geo-coded data analyses and Propensity Score Matching would also be relevant. Expert interviews will also form part
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Electronic Health Records research group for a medical statistician/epidemiologist to work on a highly innovative research collaboration with University of Hong Kong, funded by Innovation and Technology
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Machine learning/AI based classifiers Proficiency in coding using R and Python and other similar languages High level analytical capability Ability to communicate complex information clearly Informal
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UCL Mechanical Engineering has been a global leader in engineering education for over 170 years. As the UK’s first department of its kind, it introduced innovations that shaped modern engineering
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with current methods in this area is essential, as is the ability and knowledge to help develop new methods. The postholder will be working within a team of three at King’s College London that is working
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the supervision of Prof Amedeo Chiribiri within the Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Sciences, King’s College London. About The Role Applicants should be medically
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). • Work closely with interdisciplinary teams, including process engineers, chemists, and industry stakeholders in the consumer goods sector. • Interpret and communicate results through reports
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About us The UCL Faculty of Engineering is the largest of its kind in the UK, ranked as the second most impactful engineering faculty in Europe and first for Research Strength in the Research