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-depth understanding of data and related algorithms, data analysis, and machine learning. Our cross-cutting theme is machine learning-enhanced computational engineering. You’ll have an excellent
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diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community. The Electric Drives Group is seeking two postdoctoral researchers to develop
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developing computational algorithms and theory grounded in notions of information geometry and Riemannian geometry to enhance Bayesian statistical inference and machine-learning related methods. We are part of
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the development of innovative mathematical and computational algorithms. As our new Postdoctoral Researcher, your main responsibilities will include: developing and implementing advanced mathematical and
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teaching merits and, if necessary, a teaching demonstration. Additional evaluation criteria for this position are: Experience in some area of computer science represented at the department (algorithms
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their repertoire. If they encounter text written in a language they have not seen before, they label it with what their algorithm deems the closest match. The results of such behavior can vary from the indicated
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collaborators. Your work will develop algorithms, inference methods, and frameworks to adapt models from training data to test environments, which is necessary to resolve distribution shifts, hidden confounders
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teaching merits and, if necessary, a teaching demonstration. Additional evaluation criteria for this position are: Experience in some area of computer science represented at the department (algorithms
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project is to develop a high-performance computing framework for mass spectrometry proteomics to enhance efficient processing and interpretation of large datasets using deep learning algorithms and GPU
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concerned with optimal transport for inverse problems. Optimal transport for inverse problems One of the central topics of the research projects is the further development of theory and methods