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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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algorithms in the field of welding technology. Joining three different metal sheets using resistance spot welding (RSW) presents researchers with challenges. We are tackling these as part of a public research
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combine electronic components, micro and nano sensors and actuators with interfaces for communication. Fraunhofer ENAS develops individual components, the technologies for their production as well as system
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an extensive safety analysis and calidation of perception algorithms in automotive. Through our work, we lay the foundation for a reliable digital future. What you will do In our Trustworthy Digital Health group
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assistance systems Collaboration in the development of AI algorithms (LLM, fine-tuning, RAG, AI agents, embeddings) Literature research on the topic of AI What you bring to the table Studies in
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. Such multimodal energy sources will become increasingly vital over the next decades, not only as sources of renewable energy but also for high-tech applications, such as powering unattended wireless sensors
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priming and susceptibility to infections. The project aims at understanding how endogenous nucleic acids can contribute to the basal activation of innate sensors. Our group previously studied the role
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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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tasks Further development of the sensor based on aerosol separation technique and field effect transistor Use aerosol measurement technique, electron-beam lithography and cleanroom equipmen Design of
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to excel not only in computing and communication but also in handling sensor and security functions seamlessly. This requires exploration of advanced materials and their technological implementation in