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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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. Work with T&D software (e.g., OpenDSS, PSS/E) to gather data, run simulations, and assess grid-wide impacts. Additionally, candidates will: Collaborate with multidisciplinary teams to develop innovative
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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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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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The Nuclear Science and Engineering (NSE) Division is seeking a postdoctoral appointee to develop computational methods and computer codes to model the physics and engineering of advanced nuclear
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, fabrication, and measurement. Experience with microwave-optical transducers. Experience with dilution refrigerator operation and cryogenic experiments. Job Family Postdoctoral Job Profile Postdoctoral Appointee
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Applications are invited for post-doctoral positions in the Cosmological Physics and Advanced Computing Group (CPAC) Group in Argonne National Lab. Research at CPAC covers theory, modeling