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Field
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areas will be considered when selecting candidates: Machine Learning, Neural Networks, Numerical solutions of Partial Differential Equations and Stochastic Differential Equations, Numerical Optimization
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-predictive control and optimization strategies, run high-performance numerical experiments, analyze data, and communicate your findings through journal publications and conference presentations. The ideal
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-predictive control and optimization strategies, run high-performance numerical experiments, analyze data, and communicate your findings through journal publications and conference presentations. The ideal
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experimental PhDs and Canon Production Printing to enable data-driven ink optimization. Why Join? Work in the multidisciplinary Processing and Performance of Materials group Work at the forefront of sustainable
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-VLMs, tiny-VLAs; Agentic-AI systems; and Robust Generative AI targeting hallucination, safety and security issues. Besides robustness, systems should also be optimized for high performance and energy
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 2 hours ago
the U.S., and (3) optimize produced water disposal operations to maximize stored volumes. The postdoctoral research fellow selected for this project will conduct research in collaboration with NETL federal
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, modelling, fabrication, prototyping, measurements or experimental validation. Additional merits include machine learning, optimization, signal processing, numerical acoustic simulation (for example FEM/BEM
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 2 hours ago
underground natural gas storage operations in the U.S., and (3) optimize produced water disposal operations to maximize stored volumes. The faculty research fellow selected for this project will conduct
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, safety and security issues. Besides robustness, systems should also be optimized for high performance and energy-efficiency to realized efficient Embodied/Edge-AI implementations. A key focus will be
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motivation to enhance our multidisciplinary research at the intersection of control theory and machine intelligence. Methodologies of interest include: Robot modelling, Nonlinear and Optimal control