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in Robotics, including its application to advanced manufacturing, repair and non-destructive testing of composite materials, biomechanics and biomedical devices, physics-based machine learning and
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advanced manufacturing, including composite materials manufacturing, biomechanics and biomedical engineering sciences, physics-based machine learning and artificial intelligence modeling and controls, energy
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candidates with expertise in theoretical foundations of artificial intelligence, including statistical/machine learning theory, optimization, and deep learning. Successful candidates must have a strong record
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- Denver Millions of moments start at CU Denver, a place where innovation, research, and learning meet in the heart of a global city. We’re the state’s premier public urban research university with more than
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We are seeking a highly motivated doctoral student to develop ship physics-integrated machine learning models for real-time prediction and optimization of wind-assisted ship propulsion systems
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candidates with expertise in discrete mathematics, with particular interest in candidates whose research advances the mathematical foundations of artificial intelligence, machine learning, and quantum
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: https://www.utrgv.edu/research/about/center-and-institutes/index.htm . About UTRGV: UTRGV serves the Rio Grande Valley and beyond via an innovative and unique multicultural education dedicated to student
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State University of New York University at Albany | Albany, New York | United States | about 8 hours ago
, and/or mental health disorders. Candidates should employ modern research approaches such as Optogenetics, Chemogenetics, 2-photon imaging, genetic mouse models, or machine learning methods. Ultimately
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
from exceptional candidates in all areas of computer science, including but not limited to machine learning, natural language processing, computer vision, graphics, augmented/virtual reality, medical
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expertise in applying cutting-edge techniques (e.g., molecular genomic, computational, AI/machine learning tools, and/or precision agriculture technologies) to address both basic mechanisms and practical