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Sciences, who develop, manage, and refine machine learning techniques for identifying copyists; Participation in the dissemination of research results through presentations and publications; Data management
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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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intersection of Mathematical Finance, Stochastic Analysis and Machine Learning. The research areas cover a wide range of challenging topics such as (infinte dimensional) stochastic analysis, affine and
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to foster interdisciplinary learning and support young talents in shaping the future of Human-Computer Interaction in an applied setting. There is an optional combination with master thesis projects.
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sciences and artificial intelligence, and translate your findings to improve human health? Are you excited to develop and use machine learning approaches to gain new understanding of the molecular physiology
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successful candidate is expected to participate in the research projects of the Dellago Group currently focusing on the development of rare event simulation methods and machine learning approaches to study
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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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engineering, energy informatics, or a related field Solid programming skills, ideally in Python, and experience or interest in data analysis, machine learning, modelling, or simulation of energy systems
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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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to the department Ph.D. program and will work on the development and analysis of statistical methods for machine learning, particularly in the context of high-dimensional models and with a particular focus on methods