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well as in generative techniques for multi-modal images. The incumbent will contribute to novel algorithm development, detailed performance characterization and analysis, and trade studies involving
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state of the art research in computer vision, 3D processing, sensor fusion, machine learning, and other techniques to a real world outdoor ground robotic system. We emphasize regular field testing where
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, measurement techniques, and algorithms in support of applications from a broad user base. This role resides in the Advanced Detection and Applied Data Science (ADADS) group, Nuclear Structure & Advanced
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University in St. Louis. She interned at Johns Hopkins Applied Physics Lab developing image motion algorithms for a visual prosthetic. She received her doctorate in electrical engineering from Stanford
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significant usage of 6-DOF guided flight models to connect component flight, control, and sensor models and understand their performance as a system. Hardware-in-the-loop (HIL) is used to study prototype CASs
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diagnostic tools, automation, advanced software, and sensors and controls among others). Interact and collaborate with researchers from universities, national laboratories, and private industry. Present
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for advancements in critical DoD areas, such as integrated hypersonics, directed energy, advanced materials, trusted AI and autonomy, robotics, FutureG, human-machine interfaces, and integrated sensors. We
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to support data sharing across multiple agricultural sites using networked edge devices. Develop AI algorithms for distributed deep learning that optimize training time and ensure data privacy when processing
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wide range of applied research and development projects involving sensors, lasers, and electro-optical technology. ARL is an authorized DoD SkillBridge partner and welcomes all transitioning military
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focused on sensor-based in-situ process monitoring, data correlation to end part quality, data driven machine parameterization, and data management solutions. This position will perform research designed