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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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applications. With guidance, the appointee will: Develop advanced multiscale, multiphysics simulation tools relevant to the modeling of processes involving combined nuclear, chemical, and electrochemical
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decarbonization applications. With guidance, the appointee will: Develop advanced multiscale, multiphysics simulation tools applicable to the modeling of chemical processes and equipment relevant to chemical
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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of molecular reactions occurring at the surface of various materials. In addition, computational fluid dynamics (CFD) simulations combined with microkinetic modeling will be carried out to study the heat
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capability and scalability of multi-scale and multi-physics simulation codes. Develop turbulent combustion models for predictive CFD simulations of combustion dynamics in rotating detonation engines (RDEs
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A postdoctoral position on exascale atomistic simulations, AI/machine learning and data analysis of ferroelectric devices is available immediately at the Center for Nanoscale Materials (CNM
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The Environmental Science Division at the Argonne National Laboratory is seeking a postdoctoral scholar to conduct model simulations with high-resolution global and regional climate models
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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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simulation laboratory as well as supporting ongoing DOE projects. Candidates will be required to work in at least 4 of the following areas: Develop a functioning test bed using Opal-RT PHIL real-time platform