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Field
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of the bioprinting process. Objective 2: Training of a deep learning model to predict inputs that will achieve bioprinted scaffolds with the required print fidelity and scaffold micro-architecture. Objective 3
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into the generation process. This multidisciplinary project will deliver deployable models, reproducible methods, and, where allowed, shareable datasets. The student will gain training in deep learning, AI, image
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processes that produce energy and raw materials. The Department of Thermodynamics of Actinides is looking for a PhD Student (f/m/d) - Machine Learning for Modelling Complex Geochemical Systems. The job
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Kusterer), marketing strategy (Gerrit van Bruggen), deep learning (Sebastian Gabel), consumer and firm networks (Xi Chen), customer analytics (Aurélie Lemmens), and consumer learning (Maciej Szymanowski
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, Artificial Intelligence, Machine Learning or Cybersecurity or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses in, for example, Machine Learning, Deep Learning
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. We are working
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key to revealing how the brain tracks, processes, and learns auditory information. Methodologically, the project will explore the integration of information-theoretic decompositions, deep neural
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experience in artificial intelligence and machine learning is expected, but not required. Knowledge and experience in deep learning and generative AI is considered an advantage. Undergraduate research
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the intersection of ecology, machine learning, and sustainable land management, the research will combine field data collection, deep learning model development, and stakeholder co-design to support biodiversity
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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify