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Position: Lecturer A/B in Health and Biomedical Data Analytics
Institution: University of Surrey
Location: Guildford, Surrey, United Kingdom
Duties: The University of Surrey is an international university with an excellent teaching and a research profile that is innovative, forward thinking and achieving notable impact. The expanding Faculty of Health and Medical Sciences, is building capacity in Health and Biomedical Informatics to deliver cutting-edge research across key themes underpinning the University of Surrey’s Research Strategy, including Innovation for Health and Digital Innovation. We invite applications for a new university lecturer position to develop research and deliver teaching in health data analytics, AI and informatics
Requirements: Potential candidates will have demonstrable experience in real-world clinically-relevant data, informatics techniques, data sciences, and statistics. These may include method in Artificial Intelligence, statistical modelling, epidemiology, bioinformatics, data linkage and data mining, as well as insights or experience of where and when to include novel machine learning and other advanced techniques
   
Text: Lecturer A/B in Health and Biomedical Data Analytics The University of Surrey is an international university with an excellent teaching and a research profile that is innovative, forward thinking and achieving notable impact. The expanding Faculty of Health and Medical Sciences, is building capacity in Health and Biomedical Informatics to deliver cutting-edge research across key themes underpinning the University of Surrey’s Research Strategy, including Innovation for Health and Digital Innovation. We invite applications for a new university lecturer position to develop research and deliver teaching in health data analytics, AI and informatics Potential candidates will have demonstrable experience in real-world clinically-relevant data, informatics techniques, data sciences, and statistics. These may include method in Artificial Intelligence, statistical modelling, epidemiology, bioinformatics, data linkage and data mining, as well as insights or experience of where and when to include novel machine learning and other advanced techniques
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