10 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "FEUP" PhD positions at UNIVERSITY OF VIENNA
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PhD should be within the areas of expertice of the laboratory for Cognitive Research in Art History (https://crea.univie.ac.at/). Your future tasks: This is part of your personality: Above-average MA in
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survey data Development and implementation of experimental studies Writing and contributing to scientific papers for peer review Presentation of findings at national and international conferences Travel
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: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 31.01.2030 Reference no.: 5037 We invite you to join the Operational Quantum Information Team (Dakić Group
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(Master / PhD / Postdoc). Our expertise lies in quantum foundations, quantum information theory and quantum technologies. For additional information, please visit: https://dakic.univie.ac.at/ . Your future
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100 members is part of the Faculty of Earth Sciences, Geography and Astronomy at the University of Vienna. The research group “Data science in Astrophysics & Cosmology” is looking for three highly
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at the Faculty of Life Sciences seeks to appoint a pre-doctoral researcher with expertise in archaeology/archaeological science and to work with Associate Professor Katerina Douka (https://doukalab.univie.ac.at
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) on this 4-year position, you will be part of the research group “Quantum Information Science and Quantum Computation”, led by Univ.- Prof. Dr. Philip Walther. The group is part of the Quantum Optics, Quantum
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at the University of Vienna. In particular, we offer a position for a university assistant (pre doc) in the Group of Univ.-Prof. Dr. Thomas Hummel at the Department of Neuroscience and Developmental Biology. Our
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) on this 4-year position, you will be part of the research group “Quantum Information Science and Quantum Computation”, led by Univ.- Prof. Dr. Philip Walther. The group is part of the Quantum Optics, Quantum
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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 from