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: Developing innovative methods from the field of machine learning for biomedical data, e.g., explainability, interpretability, and causal inference Contributing to the design of novel algorithms and models
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Contribute to the development of new algorithms and methods for the efficient analysis of large-scale omics datasets Participate in workflow automation and management using systems such as Snakemake
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edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations
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locations in Frankfurt am Main and Berlin, DIPF develops and documents knowledge about education and thus supports science, politics and practice. The Information Center Education (IZB) department is looking
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or to: TU Dresden, Chair of Algorithmic and Structural Graph Theory, Prof. Daniel Neuen, Helmholtzstr. 10, 01069 Dresden, Germany. Please submit copies only, as your application will not be returned to you
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Description In the Department of Nuclear Medicine, we are interested in the development and clinical translation of molecular imaging tools for various applications, such as oncology, regenerative
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, regionally anchored top university as it focuses on the grand challenges of the 21st century. It develops innovative solutions for the world's most pressing issues. In research and academic programs
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the 01.02.2026 at the following conditions (PhD position): 50% = 19,92 hours Pay grade 13 TV-L limited 30.11.2028 Your tasks: Develop AI algorithms for real-time fault detection, fault classification
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SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file to kerstin.achtruth at tu-dresden.de or to: TU Dresden, Chair of Algorithms, Prof. Dr. László Kozma, Helmholtzstr. 10
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Ingolstadt. The salary is prescribed by the framework of the collective agreement (TV-L), Level 13 (75%). The research group Reliable Machine Learning (headed by Prof. Felix Voigtlaender) is part of