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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 20 days ago
chemistry, and flight-line optimization strategies to directly guide target site selection and campaign design for future PANGEA airborne deployments across tropical America and Africa. Data and Methodology
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of energy materials Develop and optimize advanced X-ray optical concepts with emphasis on maximizing photon flux, transmission, stability, beam quality, and experimental flexibility Design next-generation
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applications, or transitions to faculty. The position is optimal for applicants wanting to a) link multi-omic patient results to mechanistic, causal biology; b) eager to integrate wet-lab experiments with
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supporting materials must be uploaded as PDF files so the document can be searched by Zintellect's search engine. Scanned items are not optimal for search engines. PDF must not require special certificates
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files so the document can be searched by Zintellect's search engine. Scanned items are not optimal for search engines. PDF must not require special certificates or passwords to open. Max file size is 10MB
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and reinforcement learning for real-time optimization, fault self-recovery, and production scheduling in industrial processes. Publish research results in top-tier international conferences and journals
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, shape, and optimize granular composite (catalytic) materials that combine electrical conductivity, mechanical robustness, and fluidizability for EBFBR. Composite formulation and processing routes (e.g
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focused on the use of enabling technology, such as flow, to control complex chemical processes. With projects in supramolecular synthesis, organic materials, industry processes, automated optimization, and
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developing, optimizing, or troubleshooting complex experimental or computational workflows. Experience working in a collaborative or multidisciplinary research setting. Experience mentoring or training
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; • Familiarity with statistical analyses and modeling as well as machine learning approaches, supported with strong skills in computational optimization of methods; • Experience working with large-scale datasets