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executed. In close collaboration with PhD researchers and project partners from TUM and ETH, you will contribute to the development of novel control and learning methods for aerial manipulators and multi
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sciences.Tackling key problems in biology will require scientists trained in areas such as chemistry, physics, applied mathematics, computer science, and engineering. Proposals that include deep or machine learning
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of the following: computational analysis of human movement and/or vocalization, time series analysis, pattern finding, statistical modelling, audio feature extraction, music information retrieval, machine learning
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 14 days ago
-scale neuroimaging datasets. Responsibilities for this position includes: * Developing deep-learning approaches for insight and analysis about mouse behavior from video * Machine Learning: use your
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) conferred by start date Demonstrated experience with imaging and/or video datasets Training and experience in machine learning, computer vision, and deep learning methods Excellent English language
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. · Strong background in machine learning/AI and hands-on experience with large, heterogeneous datasets. · Practical experience with computer vision and/or spatio-temporal modeling (object detection
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this project include intraoral catheter fluid delivery, video monitoring of facial responses (i.e., gapes), operant conditioning (Med Associates), telemetry for anterior digastric muscle activation (DSI, Harvard
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. The fellow will also work closely with SCEC Senior Machine Learning Engineer Dr. Lauren Klein Dubin, who will provide day-to-day supervision of the fellow's technical work. The fellow will have opportunities
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, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100