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Field
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, and remote-sensing data) to support model benchmarking, parameterization, and uncertainty quantification. Explore and apply AI/ML approaches (e.g., machine-learning emulators, surrogate modeling, AI
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, and remote-sensing data) to support model benchmarking, parameterization, and uncertainty quantification. Explore and apply AI/ML approaches (e.g., machine-learning emulators, surrogate modeling, AI
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uncertainty quantification, global sensitivity analysis, parameter identifiability, surrogate modeling, or Bayesian model selection and comparison. Experience contributing to open-source scientific software
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mathematical background Core skills: Probability and statistics. Estimation, Bayesian inference, uncertainty quantification and calibration (proper scoring rules, reliability diagrams, ECE), experiment design
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for environmental pollution sciences. It focuses on robustness to distribution shifts, degraded inputs, and out-of-distribution conditions, while also addressing uncertainty quantification, explainability, fairness
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for Bayesian inference, inverse problems, uncertainty quantification, and scientific machine learning, with applications in environmental, scientific, and industrial imaging. The role/Te mahi We invite
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probabilistic forecasting models, including uncertainty quantification. Automation of forecasting processes, covering data preparation, model training and updating, forecast generation, performance monitoring
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Biophysical and Biomedical Measurement Group - NIST | Gaithersburg, Maryland | United States | 26 days ago
processing, internal standards/calibration, and uncertainty quantification. - Experience with spectroscopy, chromatography, electrophoresis, fluorescence methods, or complementary molecular characterization
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, race, gender, religion, marital status and family responsibilities, or disability. Key Responsibilities: The candidate will study theoretically forward and inverse uncertainty quantification problems
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/research/air-water-and-landscape-science ). Duties The PhD project will focus on uncertainty quantification in modelling flow and solute transport in fractured rocks. The work will include numerical