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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
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 20 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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University We are looking for a highly motivated postdoctoral researcher with a strong interest in optimization. The position will involve the development of novel reformulation and algorithmic methods
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computing and artificial intelligence. Areas of interest include, but are not limited to, the following: Quantum Machine Learning and AI: Develop novel quantum algorithms and computational frameworks
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development of advanced cryogenic calorimeters and associated electronics for the next-generation neutrinoless double-beta decay search. Support the development of Artificial Intelligence (AI) algorithms
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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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was created to advance research in the mathematical, algorithmic, and statistical foundations of data science and their application to other disciplines. In addition to providing support to core foundational
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building autonomous (self-driving) laboratories or integrating instruments with Bayesian optimization or other decision-making algorithms Experience with ROS/ROS2 and with robot arms (UR, FANUC, or similar
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machine learning techniques to raw ultrasound data. The project involves developing novel algorithms that integrate physics, engineering, and AI to extract meaningful and clinically relevant information
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, and development of algorithms for real-world clinical data. The fellow will have the opportunity to work with clinicians, engineers, data scientists, trainees, and research staff in a highly