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cloud data using state-of-the-art techniques (e.g., image processing, machine learning) A significant fraction of the work will be focused on the maintenance and strategic development of the group's
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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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computer-aided chemistry or an equivalent qualification Experience in the area bioanalytical chemistry Initial experience in scientific writing Didactic competences / experience with e-learning IT user
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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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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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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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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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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
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University Computer Center, Research Services and Career Development), as well as Data Stewards from other faculties/centres, you will further develop the RDM at FGGA and University. You can expect a diverse