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the challenges of dynamic sensor networks for sleep management. Through the joint supervision between multiple disciplines, the student will be offered a unique opportunity to develop a robust personal portfolio
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This PhD project focuses on strengthening network security for large-scale distributed AI training. As training increasingly spans multiple data centers connected over wide-area networks, it
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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and
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Project descriptionAutonomous systems are intelligent agents—such as robots, vehicles, or drones—that can sense their environment, make decisions, and act independently. When multiple such agents
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students and senior researchers from multiple disciplines to tackle challenges in sustainable aluminium through AI-driven microstructural analysis. The NEST-WISE project offers a vibrant collaborative
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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highly automated, networked mobility, featuring international collaboration with mentors from the USA, Asia, and Europe. TUD and the RTG embody a university culture that is characterized by cosmopolitanism
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automated, networked mobility, featuring international collaboration with mentors from the USA, Asia, and Europe. TUD and the RTG embody a university culture that is characterized by cosmopolitanism, mutual
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collaborative project that spans multiple continents. You will contribute to the development of new chronobiological analytics on existing data, design experiments to collect novel chronobiological data, engage
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use by the group employ multiple-input multiple-output (MIMO) technology and can be connected to build a distributed and cooperative network. To develop signal processing techniques, the group