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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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of existing algorithms and also to provide estimates of how this performance changes with different implementations, including predicted future hardware. Object identification and tracking can often be made
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/Associate/Full Teaching Professor (a non-Tenure-Track faculty position) in Boston, MA with general areas of focus in Artificial Intelligence, Machine Learning, and Natural Language Processing. In this role
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modern clinical trial design, such as Bayesian Adaptive Clinical trial design or established expertise in statistical methods such as structural equation modeling, causal data analysis. Experience in
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of Medicine at the University of Houston invites applications for a faculty position in the field of biostatistics and as a (non-tenure track open rank clinical faculty) Senior Biostatistician within the Humana
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tracking multiple objects by modelling the interactions between them in the presence of uncertainties, e.g. for the sensor characteristics and environment. A combination between Bayesian methods and