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Max Planck ETH Center for Learning Systems | New Germany, KwaZulu-Natal | South Africa | 27 days ago
Computer Vision robotics Autonomous Systems Causal Inference Reinforcement Learning Probabilistic Models Statistical Learning Theory Application Instructions Please submit your application through
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substantial contributions to solving the major challenges of our time, climate change and digitalisation. Our Center for Vision, Automation & Control located in Vienna invites applications for a
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Job Description Are you excited about scientific AI and developing efficient computer vision methods for analysis of complex 3D scans of natural heritage samples? Join our interdisciplinary team as a
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machine intelligence, core areas of computer science that are increasingly unified by the central role of data. The new professor will contribute to the department's vision of Trustworthy and
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and innovate, our actions together, large and small, contribute to a better world. We look forward to receiving your application! We are now looking for 1–2 PhD students for the Division of Computer
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intersection of artificial intelligence, computational biology, and computer vision. It is designed for candidates excited about applying advanced AI methods to frontier problems in biology. We are seeking
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University of California, Los Angeles | Los Angeles, California | United States | about 16 hours ago
Scholar with strong expertise in computer vision, multimodal AI, machine learning, and/or agentic AI to help build the next generation of intelligent digital health solutions. You will work side by side
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learning; experience with 3D data or point cloud processing, computer vision, or generative models is a plus. Enjoyment of application-oriented challenges in industrial contexts, translating theory
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 24 hours ago
and fluid properties in the subsurface formations. Therefore, the objectives of this research project include two aspects: (1) based on the cutting-edge technologies from deep learning, computer vision
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, including discrete and continuous decoding of hand and finger activity Develop egocentric computer-vision methods for understanding hands, objects, hand–object interactions, contacts, affordances, and task