48 parallel-and-distributed-computing-"Meta"-"Meta" Postdoctoral positions at Argonne
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turbulent combustion applications, as well as parallel scientific computing. Knowledge of deep machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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Electrical Engineering, Computer Science, Operations Research, or a closely related field. Experience in power systems, distribution systems, or microgrid modeling, with a solid understanding of advanced co
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development. Knowledge of parallel scientific computing. Ability to meet project needs and tight deadlines. Present and publish results in peer reviewed papers and/or journal articles. Skilled verbal and
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ability to scale models using distributed computing environments. Excellent oral and written communication skills for effective collaboration across multiple teams. Commitment to embodying the core values
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, AC and DC power sources, power electronic converter modules, battery energy storage system, and AC/DC loads. Develop MATLAB/Simulink models for distribution and transmission systems that include
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, computational physics and x-ray science. The appointee will benefit from access to world-leading experimental and computational resources at Argonne including some of the world’s largest supercomputers (Polaris
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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We invite applications for a Postdoctoral Appointee to contribute to a growing research program in process systems modeling and optimization for clean energy, critical materials, and advanced
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phenomena Create new reduced-order models and submodels related to fluid flow, heat transfer, thermochemistry, and electrochemistry in multiphase systems Use modeling tools such as computational fluid