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for observational research. The successful candidate will be part of Discipline 1 (Surveillance, Epidemiology, Electronic Health Records Research, Big Data). The post-holder will have a postgraduate degree, ideally a
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, requests and issues. Accuracy and integrity of data in business systems. Development of relationships within and outside the team, and positive feedback from colleagues. Compliance with processes, procedures
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experience of data management and analysis of large and potentially complex datasets and understanding of data quality and data security and encryption for transfer and storage of confidential datasets
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, organise and upload data and monitor databases and platforms. Process invoices and input financial data into systems to support the tracking of team/ department budget. Proactively review relevant process
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resolution of enquiries, requests and issues. Contribution to the achievement of team targets. Accuracy and integrity of data in business systems. Development of relationships within and outside the team
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to understand, use, and manipulate financial information. Focus, energy, drive, and ambition. Ability to prioritise and meet deadlines. Fluent in written and spoken Arabic and English. Why London Business School
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issues. Accuracy and integrity of data in business systems. Development of relationships within and outside the team, and positive feedback from colleagues. Compliance with processes, procedures and
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. Timely response to and resolution of enquiries, requests and issues. Accuracy and integrity of data in business systems. Development of relationships within and outside the team, and positive feedback from
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and contribute to methodological and applied projects in risk prediction using electronic health records data. There is increasing interest in blending concepts of causality into risk prediction models
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in working with large-scale electronic health records (EHR) data, and ideally with strong analytical skills. The post-holder will be expected to apply various analytical methods using EHR data