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biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run high-performance numerical experiments
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microfluidic analogs of phloem sieve plates and other plant hydraulic elements. Conduct controlled flow-pressure experiments to evaluate aspects of the theoretical predictions and quantify resistance mechanisms
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 8 hours 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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and experiences in at least one of the following areas: 1) advanced data analytics for performance prediction and risk analysis of transportation infrastructure; 2) network level optimization
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 14 hours 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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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 8 hours ago
list of 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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, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control the dynamics of microbial communities in time and space. Ongoing projects
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the development of predictive environmental control frameworks to improve productivity and resource efficiency. The candidate will be supervised by Dr. Md Sazan Rahman in conducting the research and
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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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of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in psychiatric disorders