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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 1 month ago
Designated Countries can be found at: https://www.nasa.gov/oiir/export-control . Eligibility is currently open to: U.S. Citizens; U.S. Lawful Permanent Residents (LPR); Foreign Nationals eligible
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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | about 2 months ago
process control requiring high-performance numerical tools for upstream optimization of the process PhD objectives: The CINDERELLA project aims to accelerate the mastery of the L-PBF process by considering
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encapsulation strategies to improve stability and controlled release of bioactive compounds. The project will also develop prototypes for human food, pet nutrition and cosmetic applications to validate
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transfer This research combines advanced numerical simulation and artificial intelligence to develop predictive models for high-temperature multiphase flows, with specific relevance to steel casting
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difficult to predict. Please review courses offered in the department and indicate which ones you believe yourself to be qualified to teach. Classes most often in need of an instructor include: CFS 31 (Family
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Control License (may be obtained within first 6 months of employment). Desired Demonstrated successful ability in taking direction, working well with others and as a leader of a team. Excellent verbal and
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. The objective of this PhD project is to develop AI methodologies for the analysis part of condition monitoring (CM) and predictive maintenance (PM). The primary challenge in predictive maintenance lies in
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patients with early DKD and matched healthy controls. ▪ Development of an AI-driven digital African twin model capturing population-specific molecular heterogeneity, disease trajectories, and predictive
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defects, are currently a major limiting factor for metal printing. In nanomedicine, various nanoparticles are used for controlled drug delivery and therapies, and laser-excited nanobubble-inducing shockwave
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and validation of a predictive pipeline for excipient–biologic interactions Integration of experimental SAXS data with AI-driven structural modeling to predict oligomerization behavior and excipient