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learning algorithms that are focused on human behavior modeling related to video classification using deep learning networks for end-users. Work with other team members to develop and maintain software
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) for science with Dr. Aleksandra Ciprijanovic (alexciprijanovic.com) and her research group! The successful candidate will join a multidisciplinary team working at the intersection of deep learning, cosmology
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computer vision tools (e.g., MediaPipe, OpenPose, homography estimation, optical flow). Experience with eye-tracking data collection or analysis. Familiarity with deep learning frameworks (PyTorch
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scientific curiosity. You thrive at the boundary of robot learning, computer vision, deep learning, and simulation, and you are excited to see your research running on real robots. You communicate clearly
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employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https://hr.northeastern.edu/benefits/ for more
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systems. Ths position requires a deep understanding of X-ray Absoprtion Spectroscopy and prior experience with methods of machine learning and artificial intelligence. A highly competitive candidate would
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etc., please see: https://csrankings.org/#/indexai&vision&mlmining&nlp&robotics&bio&world and https://mbzuai.ac.ae/study/faculty-directory/ They will work on developing Artificial Intelligence (AI) and
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of Ghent University (http://www.ugent.be/en ) and Ghent University Global Campus (http://ghent.ac.kr/ | http://www.ugent.be/globalcampus/en ) to learn more about our organizations. Center forBiosystems
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are empowered to thrive through supportive leadership, shared responsibility, and a deep commitment to genuine care and respect for our community. Find out more about our vision for a truly inclusive workplace in
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environment to study these topics given its expertise in Machine and Deep Learning, Computer Vision, Signal Processing, and Multimedia. Also, its declared vision to work especially in presence of imperfect data