705 computer-science-programming-languages-"St"-"FEMTO-ST-institute"-"St"-"St" positions in Austria
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education in the mathematical sciences. It consists of active research groups in a wide range of fields, starting from logical foundations, bridging all classical core subjects, and up to concrete
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Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description As Austria’s largest research and technology organization for applied
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Administrative tasks Your profile: Master's degree in mathematics, physics, chemistry or a similar qualification good programming skills good knowledge of English Ability to work independently and high motivation
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with current legal issues and developments in the field of digitalization (e.g. current issues regarding artificial intelligence, data economics, platform regulation, data protection). The willingness
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Application documents: Please submit a single PDF file (LastName_FirstName.pdf) containing the following information in English via email to the Dean of the Faculty of Life Sciences of the University of Vienna
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in the field of pharmaceutical chemistry. • Publishing research results in English-language journals. • You will independently hold courses in accordance with the provisions of the collective agreement
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the faculty’s ongoing research activities in the field of applied and computational PDEs in a coherent manner. Current research covers a wide range of applications, including biology, materials science, and
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, please sketch a doctoral research program This is part of your personality: • Ability to work under pressure • Problem solving skills • Excellent communication skills • Ability to work in a
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of the certificate of your completed doctoral and master program proof of language skills Via our job portal/ Apply now - button If you have any questions, please contact: Markus Ritter markus.ritter@univie.ac.at We
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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