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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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. This position offers an exciting opportunity to work at the intersection of HPC and AI, addressing critical communication bottlenecks and optimizing network interconnects for large-scale distributed systems
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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or more of the following: Experience with large-scale molecular dynamics (MD) simulations using software such as LAMMPS. Experience in handling and data analysis generated from multi-million to multi
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for deployment on large-scale computing resources, such as high-performance computers (e.g., Perlmutter, Aurora, etc.). This includes tasks such as automating model design, optimizing hyperparameters, and training
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diffraction, experience writing successful proposals for synchrotron experimental beam time at large scale facilities, x-ray data analysis expertise from single crystal materials. Knowledge of quantum systems
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candidates with a strong theoretical background in one or more subfields including topological materials, strongly correlated quantum systems, quantum dynamics, and quantum information theory. A particular
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-house codes and making use of high-performance computing (HPC) tools. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical, aerospace
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Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical/aerospace engineering, chemical engineering, or a related discipline. Onsite presence is required
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collaboration to advance their research. They also contribute to the Fundamental Symmetry group, Physics Division, and scientific community at large through service, but without the added responsibilities