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applying machine learning and computational methods for protein design, in close integration with experimental enzymology and biocatalysis. The tasks include: Development and application of AI and machine
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change via reform efforts inspired by Science Education Research and/or the Learning Sciences. The Post Doctoral Scholar will be expected to contribute to the design of qualitative (e.g., semi-structured
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environment? If so, the Oak Ridge National Laboratory’s Learning Systems Group within the Data and Artificial Intelligence Systems section invites you to apply to our new postdoctoral research associate
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well as interpretability of scientific foundation models. The rush to build foundation models has led to the development of large machine learning models in Astrophysics, fluid dynamics, biology, weather prediction, solar
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: Catherine Hartley) at New York University seeks a Postdoctoral Associate to work on neuroimaging and behavioral studies examining learning, memory and decision-making across development. NYU offers
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resonance imaging data among other imaging modalities, machine learning methods for prediction, treatment effect estimation, and contribute to understanding brain biomarkers of Alzheimer’s disease and their
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Center for Biologics Evaluation and Research (CBER) | Southern Md Facility, Maryland | United States | 2 days ago
with advanced machine learning approaches. The research will involve assay development, metagenomic (mNGS) sequencing, and bioinformatics analysis to advance regulatory science and enhance the safety
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for all postdoctoral scholars appointed through the Office of Postdoctoral Affairs. The FY27 minimum is $79, 056. Appointing a postdoctoral scholar with expertise in causal inference, machine learning, and
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monitoring agricultural emissions across Africa using satellite remote sensing, atmospheric modeling, and deep learning. Research Focus Estimate cropland emissions (NH3, N2O, CO2, CH4) using satellite
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze