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during the application process. Any further questions regarding this position should be addressed to Dr. Peter Mueller (pmueller@anl.gov ). Review of applicants is ongoing and will continue until
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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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the cleanroom with standard nanofabrication process flow Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time Type Full time The expected hiring range
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the Interfacial Processes Group (Chemical Sciences and Engineering Division), will use a combination of synchrotron X-ray based tools (e.g., X-ray reflectivity, tomographic imaging, x-ray diffraction, spectroscopy
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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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with computer-aided design software. Knowledge of deep machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and analysis of large datasets, and
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, electron spin resonance with a preference on skilled with probing fast-time scale (~ns to µs) dynamical processes. A background in microelectronics and solid-state physics Written and oral
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such as PyTorch and TensorFlow. Experience with high-performance computing and/or scientific workflow. Strong background in inverse problems, numerical optimization and image processing. Job Family
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science, demonstrated work in soil-based systems preferred. Knowledge of biogeochemical processes important in environmental science. Skill conceiving experiments and studies to develop new knowledge in
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using software, such as LAMMPS, and machine-learned potentials Experience in GPU programming with Kokkos An understanding of computer architecture and experience in the analysis and improvement