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oncology, infusion, radiation, proton therapy and related services, and network affiliations with hospitals in five states. Together, our fully integrated research and clinical care teams seek to discover
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers). Preferred Qualifications: Knowledge of Approximate, Local, Rényi, Bayesian differential privacy, and other
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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communication and collaboration skills Preferred: Experience with simulation-based inference and Bayesian methods Familiarity with cosmological simulations or observational cosmology ML architecture design and
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research on a project to harmonize phenological data from sources such as the National Phenological Network, herbaria, and the National Ecological Observatory Network and perform analyses to understand
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-development and refinement of conceptual models; devising management scenarios; building network models in one or more platforms (e.g., loop analysis/qpress; fuzzy cognitive maps/Mental Modeler; Bayesian belief
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, agriculture-based net emissions technologies, such as uptake and storage by agricultural soils and bioenergy production, are recognized as important components of future emission pathways to limit global
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learning, small data learning · Active learning, Bayesian deep learning, uncertainty quantification · Graph neural networks This position involves active participation in a well-funded
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areas Biomedical applications, social determinants of health or other demographic health areas Spatial microsimulation, spatially weighted regression, combinatorial optimization or Bayesian network