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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago
involves processing and harmonizing high-resolution NASA EO data. Subsequently, we will architect and train an ensemble of deep learning and statistical models capable of identifying key wildfire drivers and
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-aware multi-modal deep learning (DL) methods. At Argonne, we are developing physics-aware DL models for scientific data analysis, autonomous experiments and instrument tuning. By incorporating prior
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Post-Doctoral Position in Deep Learning for MRI Reconstruction at Yale University Title: Postdoctoral Associate, Yale School of Medicine Department/Division: Radiology and Biomedical Imaging
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Language Processing, and Electronic Medical Record (EMR) data mining. Prior experience in deep learning, biophysics or omics data analysis is essential. Preference will be given to applicants with prior training in
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
. Responsibilities for this position includes:* Developing deep-learning approaches for insight and analysis about mouse behavior from video * Machine Learning: use your expertise in statistics and machine learning
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learning, or related quantitative field. • Proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow, and JAX). • Experience in PDE/ODE modeling and numerical methods. • Strong interest in
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application of advanced deep learning models, with an emphasis on techniques such as knowledge distillation. The candidate will engage in research involving time-series analysis, including modeling, forecasting
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National Aeronautics and Space Administration (NASA) | Cleveland, Ohio | United States | about 3 hours ago
. Description: Exploration to deep space will require unprecedented levels of reliability and resilience to ensure mission success. Studies have shown that a high percentage of faults that occur onboard
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 3 hours ago
developing software to support AI-driven techniques to rapidly diagnose, track, and treat neurodisorders. Responsibilities for this position includes:* Developing deep-learning approaches for insight and
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to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, including machine learning, deep learning