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, operational, and societal constraints. The postdoc will work at the interface of reinforcement learning and computational epidemiology, focusing on the development of new reinforcement learning algorithms
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efficient transmission and robust communication. This work involves formulating rigorous analytical models, designing efficient algorithms, and establishing performance characterization methods that drive
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of algorithms and research tools. Applications will be reviewed starting September 1, 2026, and will continue to be considered until the positions are filled. Further information and application instructions
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 hours ago
acoustic propagation that are applicable to a wide range of ocean environments. (40%) Lead efforts to translate propagation and uncertainty models into computationally efficient algorithms that can be
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 6 days ago
Scaling: Developing data-fusion algorithms that combine VSWIR spectroscopy with active radar/lidar, thermal, and atmospheric retrievals to scale plot- and tower-based flux measurements to pan-tropical
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). Design and fabrication of the calibration test phantoms Developing and testing acquisition software, and implementing image analysis algorithms and localization methods. Where to apply E-mail
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. The successful candidate will assist in developing novel algorithms and integrating them into robotic platforms, helping to push the boundaries of embodied intelligence in both research and practical deployment
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for Advanced Mathematics for Energy Research Applications (CAMERA) has a new opening for a postdoctoral scholar to develop cutting-edge mathematics and algorithms to analyze complex data from Department
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the intersection between quantum information and particle physics. The successful applicant will work in Professor Carlos Argüelles’ group on the development of new algorithms to encode and process particle physics