-
models; 2. Statistical methods, analysis, and inference for large-scale computational simulator applications; 3. Uncertainty representation, quantification and propagation; and 4. Scalable data science
-
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
-
policy, environmental science, or a related field at the PhD level with zero to five years of employment experience. Technical background in economics with a focus on the mineral and energy sectors. Proven
-
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
-
. Contribute to open-source software development initiatives for Department of Energy projects. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years in
-
-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