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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Requirements Required skills, abilities, and knowledge: Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied
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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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publishing research findings. The project will be conducted in close collaboration with scientists within a team. Position Requirements Required skills and experience: Completed PhD (typically completed within
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relevant field at the PhD level with zero to five years of employment experience. Experience with deep learning frameworks (PyTorch, TensorFlow, JAX). Strong background in computational image processing and
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algorithm development in conjunction with extensive applications in the fields of nanoscience and energy-related materials. Position Requirements a PhD in physics, or closely related field. Degree must have
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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