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- “Towards digital biomanufacturing – developing physics-informed machine learning framework for the advanced multi-modular 3D bioprinting system”. Qualifications Applicants should have: (a) a doctoral
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climate change - Computer vision, e.g., colour vision, human colour vision, colour appearance models, etc. - AI technology, e.g. statistical learning, neural network learning, deep and transfer learning
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responsible machine learning and/or human-AI interaction can be integrated with music-based forms of human creativity to contribute to health and well-being. The doctoral research should address one or several
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Imperial College London and Imperial College Healthcare NHS Trust (ICHT). The project aims to transform the clinical use of electroencephalography (EEG) by developing and validating machine learning
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to investigate how responsible machine learning and/or human-AI interaction can be integrated with music-based forms of human creativity to contribute to health and well-being. The doctoral research should address
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in each crop area and learn basic agronomic, data collection, and plant breeding methodologies in trials and nurseries planted at the USDA-ARS. Learning Objectives: The project assignments will provide
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Digital Twin Framework for Smart and Sustainable Advanced Manufacturing Research area 3: Advanced Multifunctional Materials The ideal candidates would have a background in machine learning, manufacturing
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, such as, geometric/topological/algebraic data analysis, geometric/topological deep learning, Math for AI, categorical deep learning, sheaf neural networks, PINN/KAN models, neural operators, etc, and
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. In addition, you must have: a solid foundation in energy technology and a strong understanding of artificial intelligence (AI), machine learning (ML), and data-driven modeling documented experience
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at the University of Adelaide, contributing to cutting-edge research in computer vision and machine learning for space applications. This role focuses on advancing machine learning and computer vision research, with