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to analyze human gut microbiome data from large cohorts. Responsibilities Microbe-microbe and host microbe interaction analysis in multiple cohorts (n=2500) Evaluate differential fitness of specific strains in
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are looking for a candidate with a PhD in epidemiology, biostatistics, data science, medical science, or a related field, with solid statistical skills and the ability to independently manage data from multiple
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researchers to join the laboratories of Prof Michael Browning and Prof Jacinta O’Shea, to work on a large-scale project, sponsored by a Wellcome Mental Health Award. About the Role The posts are funded for 2
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) parameters and state variables. Inferring these parameters and/or states from large amounts of possibly high-resolution data leads to computationally intensive inverse problems. The team aims at developing
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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comfort and would be interested in a fixed term role to support a large project looking at developing outdoor thermal comfort models for children? If so, we would welcome your application to this full-time
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Does this sound like you? You hold A PhD degree in Artificial Intelligence, Data Science or Information Science, Language and Speech Technology or a closely related field. You have extensive experience
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means, data acquisition (primarily through individual semi-structured interviews), data analysis, and working with the research team and PPI co-researchers to interpret the data and disseminate findings
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statistical genetics techniques to analyse large-scale single-cell and genomic data. Data Analysis: Process, analyse, and interpret high-throughput single-cell and genomic data to derive biologically meaningful
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graduates of PhD programs in statistics, economics, computer science, operations research, or related data science fields. The position provides opportunities to participate in rigorous, quantitative research