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Field
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well as market and organization considerations. Education: Ph.D. in machine learning, computer science, engineering, science or related technical discipline. Experience: Expertise in developing and training AI
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focuses on translational research at the intersection of bioelectronics, healthcare-focused nanofabrication, and emerging applications of machine learning in radiology. Our team operates within a state-of
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the field of cybersecurity. Major Responsibilities Conduct high-quality research on the broader areas of cybersecurity, hardware security, privacy-preserving machine learning, and applied cryptography
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, Robotics, Computer Vision, or related disciplines. Proven expertise and hands-on experience in one or more of the following areas: large language models (LLMs), end-to-end learning, AV localization
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, and paid time off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records/compensation-tools.php CBC
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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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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discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials. Candidates who are nearing completion
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to diverse expertise and resources across leading institutions. The successful candidate will join a dynamic and collaborative research team dedicated to developing cutting-edge AI, machine learning, and
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of executive control, and contextual modulators of executive control like emotion and motivation. We use and develop advanced computational methods, including “big data” statistical methods, machine learning