107 computer-engineering-network-"https:"-"Embry-Riddle-Aeronautical-University" Postdoctoral positions in United States
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solutions for problems both local and global. Applicants must have received a PhD in engineering, computer science, urban science, or a related field. Experience in transportation, in particular related
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with an expertise in dynamical systems, stochastic processes or network dynamics in the context of mathematical biology. Prior experience with mathematical/computational neuroscience and scientific
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wide range of disciplines. Learn more about UNLV's postdoctoral scholars. MINIMUM QUALIFICATIONS This position requires a PhD Degree in Computer Science, Electrical Engineering, Environmental Engineering
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Description Postdoctoral Research Fellow in Network Physics of Plant Water–Carbon Transport at the Department of Civil & Environmental Engineering, Duke University Position Summary: The Department of Civil and
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 4 hours ago
adaptive mesh refinement, parameter selection/sampling, solver tuning, and convergence diagnostics. Computational acceleration: building emulator modules using neural operators and reduced-order models
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Professor John Harlim and his collaborators, Yan Li in the Electrical Engineering department, and Daning Huang in the Aerospace Engineering department in the area of Scientific Machine Learning. The project
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records in hydrology, AI/ML, or water resources engineering. Preferred Qualifications Experience with: LLMs, graph neural networks, transformers, or physics-informed neural networks (PINNs). Cloud computing
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of innovation, our diverse network of scholars and skilled engineers delivers groundbreaking solutions to the most pressing environmental science and engineering challenges, deepening our understanding
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, dynamical systems, statistical machine learning, and neural time-series data. The goal is to better understand principles and mechanisms underlying distributed brain network computations through the dual
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fields (e.g., nursing, psychology), non-clinical fields (e.g., engineering, informatics), or social sciences (e.g., health policy, biostatistics, epidemiology, economics, sociology). Research Focus Areas