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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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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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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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and support the local subject-specialist teachers in their native languages. The FLA assist the teachers during 12 lessons per week and help make the situation of learning a foreign language lively and
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to teach at a higher education institution in Germany) Duration education and training: 2 days (programme countries) or 5 (partner countries) to 60 days (excluding travel times) teaching: teaching duration
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learning new techniques The University of Regensburg aims to increase the proportion of women and therefore explicitly encourages qualified women to apply. The University of Regensburg is particularly
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the
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methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team orientation excellent
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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