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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
mathematics, or a related field Candidates should have expertise in two or more of the following areas: Uncertainty quantification, numerical solutions of differential equations, and stochastic processes
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reconstruction algorithms that incorporate multiply-beam coherent scattering imaging in a grazing incidence geometry to improve the spatial resolution to ultimately demonstrate the utility of the novel coherent
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geometry manipulation with computer-aided design software. Experience with coupling CFD and FEA codes. Knowledge of multi-dimensional code development (in C++/C/Fortran) for two-phase/multiphase flow and
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combustion engines. Experience with CONVERGE CFD software. Experience in geometry manipulation with computer-aided design software. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long
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with physics-informed neural networks, automatic differentiation, neural ODEs, or other physics-aware DL techniques. Skill in programming languages such as Python, C/C++, Go, Rust etc. Ability to model