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to power systems modeling and physics-informed neural networks. This research requires hands-on knowledge in science and engineering across a range of data analytics topics, as well as the ability
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computing (HPC) environments and include data assimilation techniques in a Bayesian framework. Under the guidance of a mentor, the participant will identify and integrate multiple data streams into the model
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institution systems may be submitted. Click here for detailed information about acceptable transcripts. A current resume/CV, including academic history, employment history, relevant experiences, and
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institution systems may be submitted. Click here for detailed information about acceptable transcripts. A current resume/CV, including academic history, employment history, relevant experiences, and
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of microphysiological systems or organ on a chip models for viral agents Collecting and analyzing data from a diverse research portfolio Building professional networks Expanding research and critical thinking skills
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areas. These include, but are not limited to: Developing, optimizing, and implementing multiple In Vitro lung models to evaluate the compounds that cannot be assessed using traditional animal models
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improve federal transit operations and oversight. Projects may include: Performing exploratory data analysis across diverse FTA datasets. Building and evaluating statistical and machine learning models
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place in the global energy and water cycles, and apply it to critically examining climate model results. We continue to seek new approaches and refinements in all aspects of the current Multi-satellitE
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. Our project aims to create a unified wildfire risk index that integrates observations and model data from NASA, including meteorological variables, fuel characteristics, topography, human influences
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control algorithms (such as adaptive control or model predictive control) to reliably maneuver Army projectiles to the target despite limited state information, control authority, and changing flight