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of Georgia leadership institution and is The Military College of Georgia. More details on the UNG Mission, Values, Vision, and Culture can be found at https://ung.edu/about/mission-vision-values.php
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Military College of Georgia. More details on the UNG Mission, Values, Vision, and Culture can be found at https://ung.edu/about/mission-vision-values.php Offers of employment are contingent upon completion
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to the student and administrative/faculty members as appropriate. Other duties as assigned by the program administrator. Basic knowledge of technology-mediated platforms for blended learning and computer software
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at the intersection of artificial intelligence and cultural heritage. The successful candidate will be involved in cutting-edge research and development in 3D computer vision and machine learning for the digital
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Torr on linkedin: https://www.linkedin.com/in/philip-torr-freng-frs-1085702/?originalSubdomain=uk Candidates should possess a PhD (or be near completion) in PhD in Computer Science, AI, Security, or a
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, Neuroscience, or a related field by the start date. Demonstrated expertise in computational modeling of human behavior or computer vision / machine learning. Proficiency in Python, MATLAB, or R. Strong
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, Applied Mathematics, or a closely related area. Demonstrated competence in machine learning, including experience with medical image analysis, computer vision, or related AI methodologies. Experience
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record relevant to the topic - publications in top journals or conferences (e.g. computer vision (CVPR/ICCV/ECCV), machine learning (NeurIPS/ICML), or robotics (ICRA, IROS, RSS, CoRL; IEEE-TRO, IJRR
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science, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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Military College of Georgia. More details on the UNG Mission, Values, Vision, and Culture can be found at https://ung.edu/about/mission-vision-values.php Offers of employment are contingent upon completion