184 phd-computational-"IMPRS-ML"-"IMPRS-ML" positions at University of Vienna in Austria
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doctoral/PhD degree in Computer Science, Business Informatics, or a closely related field, whereby knowledge of computer science is assumed to be a given. You have established experience in software
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computing facilities. The faculty runs the Vienna International School of Earth and Space Science (VISESS), a well-recognized doctoral school providing a platform for interdisciplinary research, transferable
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origins and development. The mission of the Vienna Doctoral School in Cognition, Behavior and Neuroscience is to enhance academic and professional development of PhD candidates, advance intellectual
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computational software development. You enjoy working in a team where you contribute your expertise and skill set to deliver an ambitious research vision and where you can contribute to the training of PhD and
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and English language. The department employs more than eighty staff and presently around 2500 students are enrolled in its Bachelor, Masters, Diploma, PhD and Teacher Education programmes. You will be
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better understand our world. Does this sound like you? Then join our accomplished team! Your personal sphere of influence: We are looking for a highly motivated and hardworking Prae Doc (PhD student) for 4
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intelligence, and high-performance computing to study metabolic networks and optimize microbes for biotechnological applications. The PhD project aims to predict the optimal compartmentalization of a production
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, which means: • Developing a third-party funded project to be submitted to a competitive programme (e.g. Marie Curie, FWF individual project, FWF Esprit) • Further developing your academic profile
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well as the late, medieval, and Neo-Latin language and literature. At the core of the program is a thorough education in Greek and Latin that enables critical evaluation of historical texts, along with
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/PhD degree in physics and/or aerosol related topics such as atmospheric sciences, aerosol chemistry or meteorology Professional expertise: Knowledge in experimental physics and laboratory and field work