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Observatory Network to model individual size distributions of macroinvertebrates and fish. This will include extensive travel to field sites throughout the US to conduct in situ metabolic scaling experiments
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candidates with strong expertise in Bayesian methods, uncertainty quantification, and/or machine learning applied to nuclear theory. The group’s research spans a wide range of topics including nuclear
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 2 months ago
also opens perspectives for applying and extending continuous Bayesian networks and bandit-based experimental design approaches to agricultural systems. Because of the computational demands of crop
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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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• Skilled in single-cell/population data analysis (e.g., GLMs, decoding) Preferred Qualifications • Background in machine learning or computational modeling (Bayesian methods, neural networks, etc