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starting date is November 2025. The topic of the PhD project will be theoretical research in discrete optimization, with a particular focus on either graph algorithms or multiobjective optimization
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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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algorithmic algebra. For more information about the TUM Department of Mathematics, please visit our website: https://www.math.cit.tum.de/en/math/home/. The position is a full-time position (100%), initially
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with several research groups working in related fields, particularly in algebraic geometry and algorithmic algebra. For more information about the TUM Department of Mathematics, please visit our website
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project team on “Participatory Algorithmic Justice: A multi-sited ethnography to advance algorithmic justice through participatory design” (PARTIALJUSTICE) to examine issues of justice and participation in
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. The project’s overarching goal is the development of digital quantum algorithms for the simulation of non-abelian lattice gauge theories. We are looking for highly motivated individuals, with the desire
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applications posted 2024/12/03, updated 2025/05/20, listed until 2025/07/15) Position Description: 2025/07/15 11:59PM Position Description The Technical University of Munich (TUM) welcomes applications for a PhD
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data analysis and develop sophisticated mathematical models for simulating power system behaviors under various scenarios. Development and Testing: Design and develop control algorithms to enhance grid
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research studies for automated image analysis. In particular, you will: Plan, develop, and implement AI/ML algorithms for pathology image analysis. Integrate multi-modal data (e.g., genomics, clinical data
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methods, machine learning algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems