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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 27 days ago
conditions is essential for designing more efficient TPS solutions (i.e., selecting optimal material systems, reducing design margins). Instrumentation, such as in-depth thermocouples and heat flux gauges, is
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development of novel traits. The successful candidate will be expected to develop and optimize protocols for various ‘omic techniques (single cell transcriptomics, proteomics, etc.) and other techniques
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, analysis, and optimization. The goal of the project is to develop methods for the synthesis and analysis of systems producing renewable fuels and chemicals; and use these methods, in collaboration with other
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, engineers, and researchers in an effort to develop medical automation research solutions. You will support various engineering and computer science aspects of research projects focused on optimizing combat
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patient-specific, predictive models using real-world clinical data. The project aims to enhance understanding of disease trajectories, optimize treatment strategies, and support real-time clinical decision
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), and cell free methods. Key Responsibilities: Development and optimization of vector constructs and expression condition characterization of protein yields and quality, and large-scale protein production
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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. If you have questions, please
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performance testing (e.g., polarization curves, EIS). Design and execute experiments for materials optimization and degradation analysis. Maintain and operate laboratory equipment, including potentiostats
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species. It can be fine-tuned for downstream applications such as predicting genetic perturbations, optimizing photosynthetic apparatus for performance, selecting top performing genotypes for various