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postdoctoral position in the area of numerical optimization. You will investigate and develop new algorithms for solving dynamic optimization problems with applications to sequential design of experiments
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The Applied Materials Division at Argonne National Laboratory has an immediate opening for a Postdoctoral Appointee. The candidate will be responsible for reviewing and developing design methods and
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. Major responsibilities include: Collaborating with an industry partner and other scientists at Argonne to design, fabricate, characterize, and optimize additively manufactured X-ray optics. Leading
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experimental results is required: TEM and FIB/SEM. Knowledge of materials science principles, theories, advanced characterization techniques, and practices for the design, analysis, and testing of candidate
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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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at Argonne. In this role, the candidate will design, synthesize, and evaluate cutting-edge electrocatalysts for converting CO2 into valuable chemicals and enabling water splitting, and perform comprehensive
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work with interdisciplinary research teams; collaborate with university, industry, and national laboratories partners; and drive innovation in science and engineering. In this position, the postdoctoral
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and testing to drive innovation from invention to commercialization. The successful postdoctoral candidate will join a team of Argonne researchers and work closely with universities, industry partners
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approaches to solve challenges that go beyond the use of pilot scale or commercialized equipment. As such we are seeking candidates that have demonstrated the ability to design and build their own experimental
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optimization with computer-aided design software. Knowledge of machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and analysis of large datasets, and