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of knowledge through formal conference and journal submissions. Finally, the opportunity will need to support demonstrations in simulation and on live systems. Qualifications: PhD in Artificial Intelligence
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dynamics Collect interview data, qualitatively code interview transcripts, and data analysis Systematically apply evaluation methods to individual projects funded by NC CASC to understand the collective
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Simulation (DNS), Large Eddy Simulation (LES), or RANS approaches. Many of our technical challenges can be found in published review journals [3]. New methods in machine learning are sought that can leverage
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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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to facilitate human-autonomy teaming through methods that increase an autonomy's understanding of a human teammate's state, preferences, and intents. CCDC ARL researchers are seeking to meet this goal
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and operationalization of advanced material systems, multi-physics high-fidelity computational methods and advanced turbomachinery concepts for future Army VTOL propulsion. It is operationalizing VTOL
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Organization DEVCOM Army Research Laboratory Reference Code ARL-R-CISD-300142 Description About the Research This research opportunity is to develop a novel method for information asset selection
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, propulsion and flight physics, communication and networking, and computational and information sciences. About Science of Extreme Materials Division (SEM) Materials and related manufacturing methods focusing
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dynamic modeling and simulation of small to mid-scale autonomous Unmanned Aerial Systems (UAS). The work typically involves implementation, validation, and application of first-principles methods for rotor
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behaviors such as high-speed object avoidance, perching, soaring etc. These structures and their associated aerodynamics have created a need for controls expertise in applying software for the stability