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for defense, aerospace, and critical infrastructure. Energy generation and storage systems modeling, optimization, and control, with emphasis on reliability, affordability, and national security. Experimental
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 12 hours ago
control, and coronagraph system modeling. Location: Ames Research Center Moffet Field, California Field of Science:Planetary Science Advisors: Natasha Batalha natasha.e.batalha@nasa.gov 650-604-2813 Ruslan
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• Real Estate • Business Innovation & Technology and Communications • The Finance & Administration organization Please visit the UW Facilities web page for more information: https://facilities.uw.edu
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to experimentally test predicted models would be appreciated. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UPR2357-PATACH-008/Default.aspx Work Location(s) Number of offers available1Company
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such as wrinkles can occur, which cause parts to be scrapped. To minimise material and energy wastage, digital models of the manufacturing processes can be developed and linked to process control and
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environment. Development of models to diagnose and predict battery performance and ageing. Participation in national and international research projects related with energy storage and its integration in
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predict the location of resources more accurately, it is necessary to model these processes jointly at the basin scale. However, directly solving geochemical equations is computationally expensive and
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on stability. Testing the model in standard stirred tank apparatus Refining the model to allow predictability between different types of apparatus. Defining an algorithm for testing enzyme stability
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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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development of model predictive control algorithms for autonomous robots. Key Responsibilities: Development of model predictive control algorithms for autonomous robots Job Requirements: A Master degree in