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integrating modeling, machine learning (ML), and advanced control methodologies. The research will focus on designing AI-driven algorithms to assess battery health, predict degradation trends, and optimize
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methodologies. The focus is on across-organ imaging, ranging from non-human primate (NHP) models to human applications. You will contribute to the development and application of state-of-the-art MRI techniques
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. This role focuses on developing and applying AI and deep learning techniques for analyzing high-dimensional omics data, identifying predictive biomarkers, and understanding cancer heterogeneity. Projects
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systems whose near-field radiative capabilities allow for focusing and localizing EM energy. Predictive models, based on EM simulations and extensive measurement campaigns, will also be developed
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flow systems and reactors Quantify model uncertainty and predictive confidence, including sensitivity and identifiability analyses Compare grey-box models against purely mechanistic and purely data
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Overall, Purpose of the Job The main tasks are to advance the use of high-fidelity modelling to improve understanding of the characteristics of the turbulent wakes that develop downstream of large
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their impact on gene expression. Contribute to large-scale modeling of engineered traits to predict performance and optimize design. Required Qualifications: PhD in the field of genomics, evolution, population
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they change through time. To translate eBird observations into robust data products we create custom modeling workflows designed to fill spatiotemporal gaps based on remote sensing data while controlling
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data from a recently completed clinical trial (https://www.nejm.org/doi/full/10.1056/NEJMoa2408114 ), you will build and evaluate multimodal machine learning models that integrate these data to predict
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 8 days ago
. Description: Ames scientists are actively involved in theoretical computation of extrasolar planet atmospheres, predicting exoplanet spectra, conducting and interpreting exoplanet observations, planning future