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. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch
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Are you passionate about cutting-edge research in Computer Vision and Artificial Intelligence? Our research group CVI2 - Computer Vision, Imaging and Machine Intelligence, headed by Prof. Djamila
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(e.g., tensor or multi-modality data). Work with other researchers and PhDs to develop AI applications related to image processing, computational imaging as well as computer vision. Lead a team of junior
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profile A PhD degree in Electrical Engineering, Computer Science, Applied Mathematics, Robotics, or a related field A competitive research record in one or more of the following disciplines: computer vision
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institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Computer Vision offers two full-time positions as Research Associate / PhD Student (m/f/x
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. The successful candidate will serve in a faculty role with teaching and scholarly responsibilities in the Nurse Educator Program (PhD Nursing) within the Barry University School of Nursing
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grades in a timely manner. Qualifications: PhD in Marine Science, Biology or appropriate discipline. Candidates with prior teaching experience are preferred, as are candidates with an active research
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PhD degree. The start date for this position is Fall 2026. Salary & Benefits: Minimum starting salary of $65,000, commensurate with experience Comprehensive benefits package including medical, vision
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University of Texas Health Science Center San Antonio | San Antonio, Texas | United States | 1 day ago
) and the PhD in Health Sciences. The proposed program supports the mission and vision of the School of Health Professions and UT Health San Antonio. UT Health San Antonio UT Health San Antonio is one
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We are excited to offer a fully funded PhD position at the Faculty of Engineering, Monash University (Australia). This project focuses on developing new algorithms to equip social robots with