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The VCC center at KAUST is looking for research scientists in Prof. Wonka's research group. The topics of research are computer vision, computer graphics, and deep learning. A suitable candidate
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, equipment storage, and organization Acquire, manipulate, convert and store analog, digital and computer-based audio and video formats Some video or audio editing as needed or as skill allows Participate in
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online calendars, are necessary. Ability to use or learn new technology is essential. Preferred Qualifications: Bachelor's degree in business. Experience working in an educational setting is desirable
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large-scale training of scientific foundation models You will collaborate with researchers across machine learning, scientific computing, materials science, and data engineering, and work with leading
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with vendors to ensure successful provision of support and maintenance in accordance with the contract. Qualifications Degree in Information Technology, Computer Science, Computer Engineering or
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YOUNG RESEARCHER IN THE FIELD OF EARLY DETECTION OF THE HEALTH STATUS OF PLANTS USING REMOTE SENSING
and features for the pre-symptomatic detection of changes in the physiological status of plants, developing, training, validating, and comparing predictive machine learning and deep learning models
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/Faculty Biological/Biomedical Sciences Engineering Medical - Research Internal Number: A-184691-26 General Description PREP Research Associate This position is part of the National Institute of Standards
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Development of FCT; Regulation of Research Grants of the Foundation for Science and Technology, I.P. (https://www.fct.pt/apoios/bolsas/regulamento.phtml.pt ); in force. Where to apply E-mail df.semedo
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Priorities: We seek applications across all AI domains, with emphasis on: Foundational AI : Machine Learning, Computer Vision, NLP, Robotics & Embodied Intelligence, Data Science. Interdisciplinary Frontiers
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Engineering or Industrial Engineering and Management) - 10 points; Others Masters – 2 points) b) Experience in applying machine learning algorithms, data preparation, normalization, feature selection, and