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venues Position Requirements Required skills and qualifications: A PhD degree completed within the last 0-5 years (or soon to be completed) in numerical analysis, applied mathematics, computational science
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Knowledge of atmospheric dynamics, process scale models, and numerical computation techniques Knowledge of data analysis Knowledge of using atmospheric observational datasets, data assimilation techniques
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
mathematics, or a related field Candidates should have expertise in two or more of the following areas: Uncertainty quantification, numerical solutions of differential equations, and stochastic processes
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the ability and motivation to develop expertise in large-scale model training and scaling on HPC systems, as well as in handling the unique characteristics of scientific data, including large-scale numerical
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experiments and corresponding data analysis. Following the successful demonstration of the technique, the candidate will collaborate with team members from material science to apply these methods to scientific