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HEP-CCE (Center for Computational Excellence) Storage Optimization. The HEP Division performs cutting-edge research facilitated through advanced detector development, high-performance supercomputing
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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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researchers including laboratory scientists, professors, postdoctoral researchers, and students, to facilitate the use of data management tools, develop data sharing protocols, and assist in the curation and
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analyze the results with the goal of quantifying the fundamental fluid mechanics of the systems and will work with computational modelers to develop a better understanding of the injection and breakup
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instrument programming. Interest in software development, in particular, expertise in C or C++ and Linux/Unix programming and Python. Familiarity with scientific productivity, as demonstrated by publications
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The Chemical Sciences and Engineering Division is seeking a Postdoctoral Appointee to mainly conduct research to develop high-energy and long-life lithium sulfur batteries under the guidance of a
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dynamics in models Present results at scientific meetings and prepare manuscripts for peer-reviewed publications Travel to the field site in North Dakota on occasion and when needed For more details on the
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heterointegration with other materials for developing energy efficient devices. The postdoctoral candidate will be a part of highly collaborative research team focusing on the synthesis and characterization aspect of
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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory is seeking postdoctoral researchers to work on distributed quantum computing. The project aims to develop superconducting
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of the models’ pre-processing, optimization, and post-processing steps. The candidate would also be expected to lead, and in some instances, support the development of additional modeling and analysis