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Field
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, 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 computational
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are required, as well as experience with machine learning, and some familiarity with the major bioinformatics tools/databases. Experience with high performance computing and protein function and/or structure
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for candidates with a Ph.D. in economics, management, political economy, or related areas with expertise either in game theory, particularly mechanism design or experimental methods and machine learning. The term
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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or, preferably, scientific machine learning (SciML). • Conducting research related to the improvement of the hygrothermal properties of cross-laminated timber. Desing and perform testing and analysis crate
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, Statistics, or related. Strong skills in machine learning and deep learning, with a fundamental understanding of LLMs. Proficiency inPython programmingand major ML/DL frameworks (e.g., PyTorch, TensorFlow
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 13 days ago
for extension based on mutual interest. We are looking for individuals with a strong theoretical and practical background in large language models, machine learning, and natural language processing, combined with
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, reinforcement learning, theoretical statistics, or related fields. Applicants should have a solid background in probability and statistics/machine learning. The postdoctoral fellow will be mentored by Alexander
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of Applied/Computational Mathematics. Research topics of interest include numerical methods for scientific machine learning and AI, and their applications to various science and engineering disciplines
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machine learning models to integrate real-time monitoring data. Collaborate with colleagues in computer science and computer engineering to develop models. Contribute to the dissemination of research