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outstanding candidates whose work lies at the intersection of statistics, machine learning, data analytics and modern AI algorithms. This includes, in particular, statistics for high-dimensional and complex
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of the candidate), in visualization and data analysis, cooperative systems, data mining and machine learning, education, didactics and entertainment computing, or Neuroinformatics. Across faculties, renowned
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approaches in Human-Computer Interaction and Contextual User Experience. The Center for Technology Experience is acting in a variety of challenging application contexts. We are passionate about addressing the
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through advanced machine learning and visualization techniques. As part of our vibrant and interdisciplinary team, together with the also newly created positions of Ph.D. Machine Learning and of Ph.D
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Tenure-Track Professor in the field of. Sociology with focus on Quantitative Social Science Research
quantitative empirical social research in sociology such as causal inference or machine learning or complex panel data analysis. We are seeking excellent applicants with an international research portfolio and
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studies. The successful applicant will get a contract as university assistant (prae doc) and will be working in the research group “Data Mining and Machine Learning” at the Faculty of Computer Science. Your
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of these methods to problems in the physics of oxides, semiconductors and their surfaces. Machine learning methods will be used to close the complexity gap. Applicants will have outstanding achievements or show
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geological field-based methods and big data applications and machine learning methods. Research focus will be on feedback processes between erosion, sedimentation, tectonics and climate, and topics could
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Materials Discovery group is looking for a postdoctoral researcher working in the field of machine learning of electronic structure and computational materials discovery. In this role you will be performing
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need expert knowledge in bioinformatic data analysis. Strong expertise in multi-omics data analysis (using R and Python) and a deep understanding of machine-learning models are must-criteria