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a Master’s degree in computer science, image analysis and machine learning, engineering physics, data science, applied mathematics, molecular biotechnology engineering, or another related field; or
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, engineering, physics, statistics, or a related field. Experience with image analysis, computer vision, scientific computing, statistics, applied mathematics, machine learning, or related quantitative
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engineering, or a closely related discipline. We are particularly interested in candidates with a strong technical background in medical image computing, machine learning, computer vision, or multimodal
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from Associate Professor Jakob Sauer Jørgensen ( [email protected] ), Department of Applied Mathematics and Computer Science, Technical University of Denmark. You can read more at https
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computer vision, ideally segmentation and/or quantification of micro-CT data experience developing deep learning-based image analysis methods experience with scientific Python programming experience
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Academy of Sciences (UCAS) Global Faculty Recruitment Beijing (CN) Faculty Positions in School of Al for Science / School of Electronic and Computer Engineering, PKUSZ University Town of Shenzhen
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The Chinese University of Hong Kong, Shenzhen | Eastern Shores, KwaZulu-Natal | South Africa | 14 days ago
Learning, Computer Vision, NLP, Robotics & Embodied Intelligence, Data Science. Interdisciplinary Frontiers (AI+X): AI for Science & Engineering, Medicine, Business, Social Science, and Generative AI
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to a maximum of 20% of full-time. Your qualifications You have graduated at Master’s level in Computer Science, Statistics, Mathematics, Electrical Engineering, or a related field, or completed
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Heinrich Heine University Düsseldorf | Düsseldorf, Nordrhein-Westfalen | Germany | about 5 hours ago
leading expert on the development of a human brain atlas at microscopical scale. She has applied deep learning, image analysis and advanced computing to develop the Julich Brain atlas and BigBrain, which
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applicants who would like to commit themselves, their achievements and productivity to the success of the whole institution. At the Faculty of Electrical and Computer Engineering , Institute of Circuits and