10 statistics "Duke University " Postdoctoral positions at University of Liverpool in United Kingdom
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of Alcohol Research and the Liverpool University Hospital Foundation NHS Trust. You will have expertise in health data, data science, statistical modelling and/ or artificial intelligence. You will be based in
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. This data will help shape paediatric-specific T2T endpoints and facilitate the development of personalized treatment strategies. You will apply advanced statistical and machine learning methods, and your
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bioinformatics, health data, data science, statistical modelling and/ or artificial intelligence. In this role, you will focus on alcohol use disorder, which is a common problem (1 in 5 people are alcohol
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and esteemed industrial and governmental partners. Your expertise in machine learning, statistical analysis and programming will drive impactful research aimed at solving real-world challenges. Why join
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be about to obtain) in areas relevant to this post (e.g. computer science, engineering, statistics, and mathematics etc.) Any applicants who are still awaiting their PhD to be awarded should be aware
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, health data science, health economics, psychology, health service research, computer science, signal processing, mathematics and/or statistics), with an excellent working knowledge of research methods in
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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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ocean warms. Biogeochemical-ecosystem models are currently used for this purpose but have difficulty scaling to the many thousands of plankton types. Statistical models do not have this issue and can be
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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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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