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Field
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-scale epidemiological datasets using statistical and machine learning methods Conduct systematic literature reviews and meta-analyses on disease dynamics topics Develop and validate predictive models
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terms of research and education, covering all aspects of computer science, including but not limited to algorithms, databases, cloud computing, machine learning, operating systems and security. Jobs
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-doctoral fellow position in the areas of machine learning, statistics, and data science. Chapman University is a nationally ranked institution offering traditional undergraduate and graduate programs in
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | 3 days ago
, machine learning and statistical methods to elevate impacts research. There is also opportunity to work at the nexus of water and agriculture, as well as in risk management for suburban landscapes. Location
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of design, computation, and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and
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Summary This position will provide technical support to data management plan development, data management, and assist Post-Doctoral Fellows with the development of machine learning methods. Organizational
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Lightweight and flexible solar cells Space deployable structures Device analysis in space environments Big data, AI, and machine learning for space solar initiatives Recruitment Attract top-tier postdoctoral
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scholar to conduct research at the intersection of robotics, controls, and machine learning. The successful candidate will help shape next-generation approaches for autonomous multi-robot systems
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by working to develop novel algorithms on finite element method, isogeometric analysis, geometric modeling, machine learning and digital twins to study various applications such as computational
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technology and develop human resources. The AI Computing Team explores the design and realization method of advanced machine learning systems by working across multiple layers, including circuits, devices