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text analysis, randomized data structures, high-performance computing, and quantum algorithms. Beyond this research, we aim to support computational thinking and computational problem-solving in the
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. Particularly advantageous Experience with modern software-engineering practices, e.g., git, automated testing, packaging, documentation and code review. Experience with GPU computing or high
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Informatics, Mathematics, or a related field (e.g. Computational Science/Engineering) Strong knowledge of machine learning, Scientific Computing (particularly linear algebra and numerics), and High Performance
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environment with access to high-performance computing infrastructure and medical datasets Publication-oriented research targeting top-tier conferences and journals An interdisciplinary environment at
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-performance computing and machine learning. • Fluency in written and spoken German and English. • High level of initiative, analytical thinking, teamwork and communication skills. How to apply
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health data to supporting the training and evaluation of large foundation models and deploying research software across high-performance computing and cloud environments. The scale and complexity of these
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design, computer architecture, and domain-specific/high-performance computing systems. • Nice to have (but not mandatory) background in one of the following tracks: full flow digital VLSI design (RTL-to
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sensitive data, such as medical diagnosis. The focus of this PhD project is to develop methods for reducing the dataset size without significantly affecting the performance of a model trained on that data
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state-of-the-art research infrastructure Access to modern computing and GPU infrastructure for the development and evaluation of LLM-, VLM-, and agentic AI solutions Research across the entire automotive
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molecular tumorboards and high-performance computing infrastructure (including NVIDIA B300 GPUs) Funding for open-access publications, international conferences and research mobility grants Support from the