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(https://cpac.hep.anl.gov/ ). The successful applicants will join a new project in collaboration with Argonne’s Computing, Environment, and Life Sciences (CELS) Directorate, focused on an effort to make
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Argonne National Laboratory in Lemont, IL is seeking a Postdoctoral Appointee in the Materials Science Division in Computational Materials Chemistry and Machine Learning. The postdoctoral researcher
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contribute to optimization of reactor and fuel cycle design. In this position, the candidate will develop computational methods and/or computer codes to model the physics and engineering of reactor and fuel
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Our mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with
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, computer science, computer engineering, data science, high energy physics, or a related discipline with 0 to 3 years of experience or equivalent Experience with designing applications that use high
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information science. While focused on this core responsibility, the candidate will be encouraged to explore novel avenues of research that complement and enhance the group’s overall objectives (e.g. spin
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, analytical and physical chemistry, as well as condensed matter physics. They will have the opportunity to work with the computational facilities and advanced instrumentation available at Argonne National
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estimates critical to materials design. In this role you can expect to: Work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne National
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of Energy projects. Position Requirements Ph.D. in Electrical Engineering, Computer Science, Operations Research, or a related field. Demonstrated expertise in control and optimization techniques
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The Chemical Sciences and Engineering Division at Argonne National Laboratory is seeking a Postdoctoral Appointee who, under the guidance of a supervisor, will be involved in determining accurate