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to study the behavior of waste forms and the performance of geotechnical barriers in deep geological repositories for high‑level radioactive waste. We investigate the release, migration, and retention
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Science in Life, Earth and Energy (HDS-LEE), we train the next generation of data scientists to tackle key global issues in domain sciences such as life, earth or energy. Learn more at www.hds-lee.de
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programming task within the thematic context of the advertised position: https://www.hpc.uni-wuppertal.de/de/peter-zaspel/challenge-in-bi-molecular-machine-learning/ Employment conditions This is a
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wide range of theoretical perspectives, methodological approaches, and links to educational practice. The interdisciplinary course program focuses on the processes and outcomes of teaching and learning
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, earth or energy. Learn more at www.hds-lee.de . Institute specific promise here. We are looking to recruit a PhD position – Co-regulation structures for large-scale single-cell transcriptomics – within
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Back to Overview Research Assistant / PhD Student (m/f/d), Machine learning chiral molecules, 75%Full PhD Working LanguageGerman, English LocationKassel Application Deadline20 Feb 2026 Starting
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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applies), preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file to mlcv at tu-dresden.de or to: TU Dresden, Chair of Machine Learning
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human interaction, learning, and emotional engagement through multisensory integration and scene understanding. Predictive and Adaptive Systems: leverage multimodal data to predict human intent, improve
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is being carried out as part of a joint project involving several universities and research institutions, Project consortium: Long-term behaviour of coupled reactive transport processes in deep