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Intelligence / Machine Learning, Computer Vision, and Natural Language Processing. Tenured faculty candidates will also be considered for this position, with a preference for full professors. Heterogeneous
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. Purpose The purpose of this position is to carry out advanced scientific research in the area of Artificial Intelligence/Machine Learning and its applications to cyber-physical systems, involving new
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medical imaging and theranostics. Expertise in fundamental and applied machine learning and artificial intelligence for advancing clinical medicine is of particular interest. About TITAN: The Texas
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Engagement Following the first year, teach one course per academic year (up to two by mutual agreement) in diplomacy, war, or intelligence studies Provide a minimum of 15 days of on-site faculty supervision
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for Generative AI, the individual will, with independence commensurate with experience, perform research within the Center for Generative Artificial Intelligence and its parent organization, the Machine Learning
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to teach undergraduate courses in Computer-Aided Design and Graphics. Based on current course loads, the position is intended to be full-time, benefits-eligible, for the fall and spring long semesters
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be authorized to work in the U.S. on a full-time basis for any employer without sponsorship. Responsibilities Teaching & Curriculum Development: Teach undergraduate and graduate courses on diplomacy
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Chair. His research interests include electronic design automation, efficient machine learning, hardware acceleration, prototyping for analog/digital/mixed-signal designs and emerging technologies. He has
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at UT Austin across the general areas of 1. Machine learning for accelerating computational modelling of materials, 2. Computer vision for advanced imaging in materials characterization, 3. Large
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of the cluster initiative is to strengthen expertise in Foundational AI to accelerate materials research at UT Austin across the general areas of 1. Machine learning for accelerating computational modelling