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scope of the PhD position(s) fall within the areas of novel low-complexity neural network architectures, generative audio techniques, and the integration of large language and speech foundation models
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fundamental and applied research within communication, networks, control systems, AI, sound, cyber security, and robotics. The department plays an active role in transferring inventions and results
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complex interaction patterns that may carry important biological information. By integrating deep learning, genome-wide simulations, functional genomics, and large-scale biobank data, AI:GENOMIX aims
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challenge: how to evolve classical communication networks to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk). CLASSIQUE will address a
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on constrained platforms using techniques such as model compression, quantization, and hardware-aware neural network design. Investigating mechanisms that protect the integrity and reliability of deployed AI
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distribution infrastructures, and heterogeneous networks and storage environments based on Cloud based services, CDNs and Edge Computing. This complex chain of delivery has negative implications
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problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control
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safer, more reliable, and more sustainable renewable energy systems. You are driven by scientific curiosity, enjoy working with complex multi-physics models, and are eager to advance probabilistic methods
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, predictive modelling, and autonomous maintenance solutions. You thrive on scientific discovery, enjoy tackling complex multi-physics problems, and have the drive to explore innovative concepts
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, enjoy tackling complex multi-physics problems, and have the drive to explore innovative concepts at the intersection of engineering, data, and emerging technologies. DTU Wind and Energy Systems, in