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Field
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scientific publications, patents, and seeing collaborators translate our work into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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writing C++ and PyTorch. Training and debugging RL agents. Imitation Learning algorithms for robotics or autonomous vehicles. Prior work combining RL with human data or feedback. A track record of code
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vision, controls, cyber-physical systems and their security, hardware security, and machine learning and their security. The work will include algorithm design, prototype implementation (e.g., in Matlab
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PhD level with zero to five years of employment experience. Expertise in testing, characterizing, and measuring MEMS devices and designing feedback loops and control algorithms for the precise operation
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candidate will design and develop digital twin algorithms for computational fluid dynamics, contributing to innovative solutions in healthcare software systems. This role involves collaboration with research
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 2 hours ago
Science Program with its UAS fleet, the Earth Science Projects Office, and the Airborne Sensor Facility, and is associated with related local capabilities in intelligent systems, supercomputing, flight
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interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific computing and machine learning. The research will emphasize both theoretical
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novel photonic techniques such as time resolved single photon technologies, spectral imaging, and optical fibre sensors to tackle clinical/biomedical challenges and other real world applications. Our work
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addition to an interest in conducting collaborative research within the focus area of the project, all applicants should demonstrate some knowledge of social media research and social media algorithms, experience with