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. We are interested in candidates with research interests in causal inference or Bayesian methodology, and we also welcome strong applicants from the broader fields of statistics and machine learning
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Bayesian hierarchical modeling with applications in transportation, urban planning, environmental science, public health, and computational social science. The incumbent will teach the standard teaching load
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awareness of AI methods. Technical and mathematical skills required for such research, regardless of prior AI experience. Relevant mathematical backgrounds including, but not limited to: Bayesian statistics
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of different forms of human, Training in radiocarbon dating and its application to archaeology, pretreatment chemistry, palaeoproteomics and the Bayesian modeling of radiocarbon dates will be given, but prior
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Centre (NCN). The Principal Investigator is Dr. Eng. Piotr Kopka, email: Piotr.Kopka@ncbj.gov.pl Project description: The project aims to develop a new class of inverse Bayesian models called STE-EU-SCALE
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physics, complex analysis, and dynamical systems. The statistics group research areas include biostatistics, Bayesian methods, environmental and ecological statistics, multivariate statistics, spatial and
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, pretreatment chemistry, palaeoproteomics and the Bayesian modeling of radiocarbon dates will be given, but prior experience would be an advantage We expect you to finalize your dissertation agreement within 12
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radiocarbon dating and its application to archaeology, pretreatment chemistry, palaeoproteomics and the Bayesian modeling of radiocarbon dates will be given, but prior experience would be an advantage We expect
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datasets. Apply sensitivity analysis, parameter subset selection, and Bayesian inference to improve model identifiability and predictive capability. Implement computational pipelines in Python, MATLAB, and
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of different forms of human, Training in radiocarbon dating and its application to archaeology, pretreatment chemistry, palaeoproteomics and the Bayesian modeling of radiocarbon dates will be given, but prior