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dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive salary in one of Germany’s most attractive research environments. TUD is one of eleven
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explored using scientific machine leaning. Machine learning, programming experience and a curious mind-set You are fascinated by how computers can learn from data and you have a strong interest in the
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to evaluate. The main research question is how to automatically harmonize the retrieved information allowing a unique analysis and to map them against multiple user-tailored outputs. This is necessary as the
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rhabdomyosarcoma), fragmented data from multiple small series has hampered global elementary understanding of metastasis biology and - therefore – targeted therapy development. It remains unresolved – and is
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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-time 65%) in the DFG-funded Integrated Research Training Group (RTG) Beyond Amphiphilicity – RTG 2670: Self-Organization of Soft Matter via Multiple Noncovalent Interactions . The position is funded from
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in AI: Generative Diffusion & 3D/4D Scene Synthesis: Re-design diffusion and NeRF-style models so multiple agents jointly reconstruct a scene. Semantic-Aware Compression & Network Information Theory
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TV-L, part-time 65%) in the DFG-funded Integrated Research Training Group (RTG) Beyond Amphiphilicity – RTG 2670: Self-Organization of Soft Matter via Multiple Noncovalent Interactions . The position