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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for a postdoctoral position in the area of uncertainty quantification and
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become part of a new holotomography software package actively being developed by the team. Position Requirements Required Knowledge, Skills, and Experience: PhD (recently completed or soon-to-be completed
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We are seeking a Postdoctoral Appointee to work in the Mathematics and Computer Science (MCS) Division of the Computing, Environment, and Life Sciences directorate (CELS) of Argonne National
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. Contribute to open-source software development initiatives for Department of Energy projects. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years in
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and oral communication skills Requirements: Recent or soon-to-be-completed PhD (within the last 0-5 years) in the field of organic, organometallic, or inorganic chemistry, or a related field Ability to
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-completed PhD (within the last 0-5 years) in the field of organic, organometallic, or inorganic chemistry, or a related field Ability to model Argonne’s core values of impact, safety, respect, integrity, and
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: 10.1038/s41467-023-39984-3 Position Requirements This level of knowledge is typically achieved through a formal education in Physics, or a related field at the PhD level with zero to five years
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PhD level with zero to five years of employment experience. Expertise in testing, characterizing, and measuring MEMS devices and designing feedback loops and control algorithms for the precise operation
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of deposition science and heterogenous interfaces. Position Requirements: A PhD in chemistry, materials science or related field; received within the last 5 years or upcoming year. Significant written and oral
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including engineering, economics, and environmental science. Experience developing mathematical or computational models for simulation and optimization of energy/economic systems in ASPEN Plus® and/or Julia