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models; 2. Statistical methods, analysis, and inference for large-scale computational simulator applications; 3. Uncertainty representation, quantification and propagation; and 4. Scalable data science
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
, or Julia) Experience in statistical modeling and probabilistic analysis Ability to model Argonne’s core values of impact, safety, respect, impact and teamwork Preferred skills, abilities, and knowledge
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. Familiarity with techno-economic analysis. Experience with scientific programming languages (e.g., R, Python, Java) and statistical software (e.g., Stata). Ability to create visualizations to effectively
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and Python) Knowledge of data analytics and statistical methods Demonstrated strong scientific writing skills and oral communication Ability to work both independently and collaboratively as a team
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software development practices. Experience with uncertainty quantification and statistical analysis Skill in written and oral communications. Experience interacting with scientific staff and research groups
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. Proficiency in frameworks like Pyomo and/or TensorFlow/Pytorch/Keras Solid foundation in mathematics/statistics, with experience in cyber-physical systems modeling. Ability to work both independently and
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-of-the-art data management, machine learning and statistics techniques. With the advancement of Exascale systems and the variety of novel AI hardware designed to accelerate both training and inference