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to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more efficient, intelligent, and impactful. You will integrate field
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- identifying which measurements are most informative and guiding where, when and how to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make
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of knowledge-driven models, leveraging Bayesian statistics and causal inference for calibrated uncertainty, distribution-shift detection, and safety guarantees. You will be will working within the Center
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of knowledge-driven models, leveraging Bayesian statistics and causal inference for calibrated uncertainty, distribution-shift detection, and safety guarantees. You will be will working within the Center