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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 15 days ago
gradients, and geomorphic transience regulate rock-derived nutrient (P, Ca, Mg, K, and bedrock N) distributions across landscape to cross-basin scales. Agricultural & Agroecosystem Dynamics: Quantifying crop
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Equation, Stochastic simulation algorithms, and approximation methods. ● Experience with single-cell or spatial transcriptomic data analysis. ● Familiarity with machine learning and deep learning
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algorithms to improve the performance of scientific applications Researching digital and post-digital computer architectures for science Developing and advancing extreme-scale scientific data management
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. The successful candidate will contribute to the design and implementation of algorithms, symbolic computation systems, data processing pipelines, and machine learning. Essential Job Duties Develop computational
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. Prepare, distribute and utilize instructional support materials, including course syllabi, supplementary materials, instructional media and other devices as appropriate. Convene classes as scheduled and
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. Preferred Qualifications: Knowledge of Approximate, Local, Rényi, Bayesian differential privacy, and other related definitions. Knowledge of federated learning SOTA algorithms. Knowledge of distributed
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electromagnetic and thermal simulations. This work will include detailed tissue segmentation from medical images, integration of automatic and semi-automatic segmentation algorithms, refinement of anatomical
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and/or Windows environments Working knowledge of modern development tools (Git, CI/CD pipelines, automated testing frameworks) Knowledge of data structures, algorithms, and performance optimization
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maintaining software in Linux and/or Windows environments Working knowledge of modern development tools (Git, CI/CD pipelines, automated testing frameworks) Knowledge of data structures, algorithms, and
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maintaining software in Linux and/or Windows environments Working knowledge of modern development tools (Git, CI/CD pipelines, automated testing frameworks) Knowledge of data structures, algorithms, and