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companion animals (SAVSNET), but increasingly from horses and farm animals that together total 100s of millions of rows of data, and use statistics, epidemiology, data visualisation and dashboarding, and
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experienced people. You will have a PhD in a relevant area (e.g. epidemiology, economics, geography, public health, psychology, data science, applied statistics), with an excellent working knowledge of research
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degree (or be close to completion) in, for example, econometrics, statistics, or computer science, with experience of analysing large datasets. The post offers the opportunity to contribute to a research
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with a diverse training background to apply e.g. epidemiology, statistics, mathematics, engineering, physics, where you can apply your knowledge to health care data. You will have a PhD in epidemiology
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with a diverse training background to apply e.g. epidemiology, statistics, mathematics, engineering, physics, where you can apply your knowledge to health care data. You will have a PhD in epidemiology
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statistical learning as it relates to biomedical applications and a desire to work collegially with researchers within the department and institute, as well as with clinical researchers to build an effective
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relevant methods are population dynamics theory (e.g. integrodifferential equation models or point process models) and Bayesian statistical methods (customising routines rather than simply using Bayesian
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during the research expedition, including hydrography, nutrients, nitrogen fixation rates, abundance and diversity of nitrogen fixing microbes gleaned from molecular analysis using advanced statistical and