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of The University of Glasgow Inference Dynamics and interaction Research group, in the School of Computing Science, including establishing and sustaining a track record of independent and joint publications
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and advanced quantitative techniques¿including fluorescence correlation spectroscopy, single¿particle tracking, time¿resolved anisotropy, cryo¿EM particle¿counting, and Bayesian fitting¿to extract
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a spatially explicit predictive model for Everglades vegetation dynamics in response to major drivers. The major objectives are to explore the distribution models that discriminate among prairie and
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can be tackled. A video describing the project can be viewed here: https://www.youtube.com/watch?v=IzPuuBnrIDc . The successful candidate will be developing Bayesian models for estimating
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computational modeling, geometric morphometrics, multivariate and Bayesian statistics, spatiotemporal and spatial modeling (including GIS), causal inference, machine learning, AI, and statistical software
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, please visit: http://uhr.rutgers.edu/benefits/benefits-overview . Posting Summary In this position, you will join an established researcher with a track-record of excellent publications and collaborative
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and PhD students. Research spans a wide range. Current interests include: Bayesian statistics; modelling of structure, geometry, and shape; statistical machine learning; computational statistics; high