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The Chemical Sciences and Engineering Division is seeking a Postdoctoral Appointee, who under the guidance of a supervisor, conducts research on mathematical modeling of solid-state batteries
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The Applied Materials Division at Argonne National Laboratory is seeking a staff Assistant Scientist in the Functional Coatings Group. The successful applicant will join a diverse and energetic team of staff scientists, postdocs, and students dedicated to advancing the science, technology, and...
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applied mathematics group is seeking a Postdoctoral Appointee to conduct research and development on differentiable and portable linear solvers tailored for advanced numerical simulations. This role will
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The Electrochemical Materials & Interfaces Group with Argonne's Materials Science Division is seeking a Postdoctoral Appointee. The purpose of this appointment is experimental studies on metal deposition (Li, Na, Zn) and the synthesis and characterization of composite polymer electrolytes and...
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engineering package (e.g. pandas). Solid foundation in mathematics/statistics with experience in cyber-physical systems modeling and analysis. Ability to work both independently and collaboratively in a team
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, engineering, applied mathematics, or another related field. Experience with C++ programming. Effective written and oral communication skills. Ability to work individually and collaboratively as part of a team
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Economics / Resource or mineral economics, Data Science, Statistics, Computer Science / Software Engineering, Mechanical Engineering, Industrial Engineering, Systems Engineering, Applied Mathematics
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or mineral economics, Data Science, Statistics, Computer Science / Software Engineering, Mechanical Engineering, Industrial Engineering, Systems Engineering, Applied Mathematics, Operations Research, Logistics
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The Laboratory for Applied mathematics, Numerical software, and Statistics (LANS) and the Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invite applicants for a
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, chemistry, physics, mathematics, or related engineering disciplines Knowledge of statistical techniques including Bayesian methodologies Interest in software development, with particular emphasis