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Field
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machine-learning and AI methods for complex engineering and industrial systems, with a particular focus on improving their reliability, availability, and operational performance while enabling more
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. Ability to effectively utilize a computer and applicable software to create databases, perform statistical analyses, present data, and perform other computer related tasks. Ability to multitask and work
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breeding program. This requires a Ph.D. with excellent knowledge and skills in drones / UAV / UAS data collection, processing, statistical analyses, AI (machine learning, deep learning) and subsequent
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qualifications Publications at top machine learning or computer vision conferences (NeurIPS, ICML, ICLR, CVPR, AISTATS etc.) are highly meriting. Expertise in Bayesian methods, generative models, multimodal models
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, computer vision, robotics, biomedical engineering, computer science, biomechanics, neuroscience, signal processing, or a closely related discipline. Strong expertise in machine learning and deep learning
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, design and implementation of an immersive training tool that leverage spatial computing, computer vision, and on-device AI to support automated feedback, skill evaluation, and scalable surgical and trauma
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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related to the project’s objectives. • Process and analyze the collected data by implementing machine learning algorithms and artificial intelligence. • Develop a web-based geospatial interface
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. The QML-CVC team (https://qml.cvc.uab.es/ ) is part of the Computer Vision Center at the Universitat Autònoma de Barcelona; the CVC is a center with over 150 persons working machine learning and computer
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have the opportunity to contribute to various cutting-edge research areas. Several exciting research topics are proposed (not limited): Computer Vision / Remote Sensing for Agriculture: Explore