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The Mathematics and Computer Science Division (MCS) at Argonne National Laboratory is seeking a Postdoctoral Appointee to conduct cutting-edge research in scientific machine learning, focusing
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knowledge of contemporary high-energy physics and mathematical methods relevant to physics applications Effective verbal and written communication skills Ability to model Argonne’s core values of impact
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The Applied Materials Division (AMD) at Argonne National Laboratory is seeking to hire a postdoctoral appointeee in the Separations and Bioprocessing group. This position will have two focus areas. One is to support an effort to recycle graphite from Li-ion batteries to produce graphene and...
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Knowledge, Skills, and Experience: Proficiency in mathematical analysis and operator theory. Experience working with microelectronics. Experience in conducting synchrotron experiments and analyzing
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approaches. Position Requirements Recent or soon-to-be-completed (typically completed within the last 0-5 years) Ph.D. in mechanical/aerospace engineering, applied mathematics, chemical engineering, or a
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Argonne National Laboratory is seeking a highly skilled Postdoctoral Researcher to work in the Separations and Bioprocessing Group on developing, designing and characterizing new polymers and membranes for gas and liquid separations. The ideal candidate will have expertise in polymer synthesis...
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in multidisciplinary teams. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Preferred Knowledge, Skills, and Experience Background in economic theories and
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environmental trade-offs. Contribute to projects involving capacity expansion, production cost modeling, and equilibrium modeling of power systems. Design and apply mathematical optimization models, including
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deposition (ALD). The project involves performing quantum mechanical calculations (e.g., first principles density functional theory (DFT)) to identify the structures and to understand the complex mechanisms
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techniques in interfacial science; and mathematical techniques and computer programming for data analysis. Considerable skill in working interactively and productively in a multidisciplinary environment Good