142 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "UCL" "UCL" "UCL" "UCL" positions at Nature Careers in Austria
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scientific excellence. Ready to be part of our team? Welcome aboard! Your personal scope: Join us at the Institute for Public and Administrative Law (Faculty of Law), led by Professor Dr. Anuscheh Farahat
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our accomplished team! Your new working environment: At the Institute for Civil Law (Univ.-Prof. Dr. Olaf Riss, LL.M.) a position as a university assistent (prae doc) is to be filled as soon as possible
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the learning and living environment of schools on the basis of scientific expertise. Your personal sphere of play: As a university assistant postdoc, you will become part of the research team around Prof. Dr
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at the Department of European, International and Comparative Law at the University of Vienna in the team of Prof. Dr. Matthias Lehmann, D.E.A. (Paris II), LL.M., J.S.D. (Columbia). We conduct excellent research and
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salary. As a university assistant prae doc, you will complement the research team around Univ.-Prof. Dr. Dr.h.c. Paul Oberhammer. The employment duration is 4 years. Initially limited to 1.5 years
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personal development. Your personal sphere of influence: As a university assistant prae doc, you will join the research team led by Univ.-Prof. MMag. Dr. Michaela Windisch-Graetz in the field of labor and
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public debate on loneliness, privacy, radicalisation and social isolation under the guidance of Univ.-Prof. Dr. Anna Durnova, Ph.D. This position is offered in the framework of the ERC Advanced Grant
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for the analysis of ONT data are expected. The successful applicant will work in the team of the Joint Microbiome Facility of the Medical Univeristy of Vienna and the Univeristy of Vienna (JMF), and support Centre
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Information Systems at the Faculty of Computer Science is looking for highly motivated research assistants, Ph.D. candidates. We are offering an excellent working environment in a young, creative, highly
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Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains