481 machine-learning "https:" "https:" "https:" "https:" "https:" "Cardiff University" PhD scholarships in Germany
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12.01.2026, Academic staff The Professorship of Machine Learning at the Department of Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%; initial contract 1.5
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. Application deadline No application deadline Submit application to Please contact the respective research group directly. https://www.uni-bremen.de/en/pip/faculty-1/institutes In case of questions, please e
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https://www.chemie.uni-bonn.de/de/forschung/bigschemistry for further details). International elements Projects with partners in Germany and abroad Special promotion / funding of the programme DFG (e.g
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(4DSTEM). This approach will combine three-dimensional charge distribution data, generated through atomistic simulations, with machine-learning-driven modelling to guide and refine the phase reconstruction
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, leveraging a principled combination of passivity-based control methods, machine learning, and human-in-the-loop systems to enable robust teleoperation in uncertain and delayed communication environments. Key
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are available in early 2025 and will remain open until filled. Further information: https://www.mls.ls.tum.de/en/plasysbio/home/ Selected recent publications Graf, A., Bassukas, A.E.L., Xiao, Y., Barbosa, I.C.R
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(https://soilsystems.net/ ), a Priority Programme (SPP 2322) funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation). Within SoilSystems, scientists from different disciplines from
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of different faiths and beliefs. Grounded in the Christian view of human life, the KU aims to create an academic and educational culture of responsibility. The research group Reliable Machine Learning at the KU
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focus is developing and characterizing metallic high-performance materials for/through additive technologies using experiments and computer-aided methods. Furthermore, the chair is dedicated
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University of Munich (TUM), you will be submitting personal data. Please refer to our data protection information in accordance with Art. 13 of the General Data Protection Regulation (DSGVO) http://go.tum.de