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, safety, respect, integrity, and teamwork. Preferred Knowledge, Skills, and Experience: Background in economic theories and their application to overall or specific energy, mining, and manufacturing sectors
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: Experience with generative models (transformers, diffusion models, VAEs, GANs) applied to biological sequences Familiarity with the theory behind modern molecular biology techniques Knowledge of HPC
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effects on fluid behavior in reacting and non-reacting flow applications. Understanding of combustion theory and modeling applied to combustion engines and other propulsion systems. Understanding of Finite
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members on the experiment sides and also work closely with our theory collaborators to establish “read” and “write” of information using this optically addressable atomic memory. The candidate is expected
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and reports describing results of development work, analyses, and investigations. Position Requirements Knowledge of nuclear engineering principles, theories, and practices for the design and analysis
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or soon-to-be-completed PhD (typically completed within the last 0-5 years) in Electrical Engineering Fundamental understanding of power system modeling, numerical methods and linear control theory
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quantum mechanical calculations (e.g., first principles density functional theory (DFT)) to identify the structures and to understand the complex mechanisms of molecular reactions occurring at the surface
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. Proficiency in frameworks like Pyomo and/or TensorFlow/Pytorch/Keras Solid foundation in mathematics/statistics, with experience in cyber-physical systems modeling. Ability to work both independently and
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physics, nuclear theory, nuclear data, accelerator R&D and operates the DOE Office of Nuclear Physics National User Facility, the Argonne Tandem-Linac Accelerator System (ATLAS). As an equal employment
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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