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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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microscopy and atom probe tomography will be prepared. Finally, you will merge the images by means of deep learning algorithms. Your tasks in detail Development of the experimental protocol for the imaging
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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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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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with the latest sensors (camera and LiDAR sensors), is available for the work. What you will do – development of algorithms for 3D multi-object tracking based on heterogeneous sensor data fusion
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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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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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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will