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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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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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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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large-scale human data (genomes, single-cell and spatial omics, longitudinal biomarkers, computer vision, electronic health data) with cutting-edge AI, we aim to fundamentally transform Parkinson’s
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Computer Vision and Learning Systems (CVL) at ISY has a vibrant research environment with a total of approximately 30 employees. This includes four faculty members, Assistant Professors, Postdocs, and PhD
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society. The Center for Vision, Automation & Control located in Vienna (Giefinggasse, 1210) invites applications for a master thesis. Within the Center for Vision, Automation & Control , the Competence
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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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, 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
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University of California, Los Angeles | Los Angeles, California | United States | about 11 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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. Publish research results in leading journals and conferences in machine learning, computer vision, and computational imaging. Contribute to research-based teaching and supervision of MSc and BSc student