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cancer in Barrett’s esophagus. Experience in analysing large datasets in R is essential but will also involve the use image analysis software such as Qpath. About You We seek an ambitious and self
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responsible for cleaning and manipulating datasets for analysis, undertaking complex statistical analyses and presenting the results for discussion and interpretation. About You The post would be ideally suited
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invasive surgery. Essential skills include system integration, Image processing, data analysis, and excellent written and verbal communication. The ability to work both independently and as part of a
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epidemiological research. Strong quantitative data analysis skills and applied understanding of epidemiological principles are required. They must possess excellent interpersonal communication skills and be
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meticulous approach to data collection, analysis and preparing manuscript for publication. A demonstrated ability to communicate well, work within a team, and deliver projects within an agreed timeframe is
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to other aspects of the quantitative analysis. Specifically this may include coordinating and maintaining close working partnerships with collaborating GP practices, patient and members of the public and key
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responsibilities will include: Pre-registering data analysis plans; Leading and conducting advanced statistical analyses (e.g., twin/family designs, genomic and epidemiological methods, longitudinal modelling
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leading on qualitative data collection and analysis for the relevant workstreams of the ADHOC programme, the main duties will include contributing towards the ADHOC Trial at all stages by applying agreed
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applicants from a wide range of disciplines proposing other or complementary approaches from those disciplines e.g. political science, public policy analysis, human geography, anthropology, sociology, critical
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performing experiments using human cells, murine tissues and/or cell lines. You must have previous experience on handling scientific data, data analysis and statistics. Must have excellent interpersonal