32 postdoctor-simulation-optimization PhD positions at Technical University of Munich
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16.07.2025, Wissenschaftliches Personal A PhD position (75% TV-L E13, to be extended to 100% after 8 months) in discrete optimization is available at the Professorship of Optimization and
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to challenging questions in the field of computational material design, especially with the help of CALPHAD-based methods. For further development of our simulation environment (https://github.com/cmatdesign
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data to answer relevant questions and solve real-world problems. It brings together fundamental, methodologically driven research in optimization, machine learning, and artificial intelligence with
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(MCQST) is inviting applications for a Ph.D. or postdoctoral position. In recent years, spin defects in diamonds have been shown to act as atomic-sized sensors for nanoscale- microscopic magnetic field
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, natural hazards management or related fields Interested in protective forests and their management Good quantitative skills (e.g., data analysis, simulation modelling, remote sensing) Good communication
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measurements in a team of experts on and in the pyramids and creating digital object models with numerical simulations, for example, using Salvus software or similar. Publication of research results and
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
geometry, algorithmic complexity, and combinatorial optimization. Our contributions are regularly published in top venues like the Conference on Artificial Intelligence (AAAI), the Symposium on Algorithms
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-selectivity. Calculations and simulations will guide fabrication of experimental prototypes, to be tested in beamtime experiments at world-leading neutron science facilities (e.g. ILL, FRM II). Experimental
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16.08.2023, Wissenschaftliches Personal The Chair of Computational Modeling and Simulation (CMS) at the Technical University of Munich invites applications for the position of a Research Assistant
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main focus on the development of control software. ▪ You will design and implement advanced control and readout protocols and optimize experimental characterization workflow,s leveraging machine learning