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research are computational models ranging in complexity from semi-empirical aero prediction models to CFD models of varying complexity. Windtunnel and free flight experiments serve to complement and validate
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? Under the guidance of a mentor and as the selected candidate, you will learn how to apply algorithms to predict parts of coding and noncoding sequences for optimization. As a result, designed mRNA
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performance, increasing the effective lift-to-drag ratio and keeping benign thermal exposure to the hypersonic vehicle structures. Under this research program, focus will be to innovate advanced gas turbine
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Organization DEVCOM Army Research Laboratory Reference Code ARL-C-CISD-300154-SIS Description About the Research This research develops computational methods that enable robots to perceive and
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Networks (DNNs) sparsity. The compute-intensive floating-point 32-bit representation represents remaining non-zero valued network parameters. These approaches need to be improved to develop a real-time
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on the energy constraints associated with their mission planning and logistics of operation. The goal of this research is to develop new techniques and algorithms that can better plan the missions of aerial and
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collection of streaming sensor data. This project focuses on utilizing state-of-the-art reinforcement algorithms to 1) dynamically learn from multi-agent actions and context, 2) evaluate the environment and
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engineering, computer science, or related fields Expertise in machine-learning and/or online BCI Advanced programming skills (i.e. Python, Matlab, R) and strong experience in algorithmic design, mathematical