241 computer-science-programming-languages-"St"-"St" positions at University of Vienna
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Limited contract until: Job ID: 4344 The University of Vienna plans to expand the existing Research Data Management services by offering discipline-specific support through a new Data Stewardship program
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personality: A completed Master's degree in Data Science, Physics, Chemistry, Computational Biology, Bioinformatics, or a related field. Strong programming skills in Python, R, or similar languages. Experience
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: The ideal candidate will have a background that combines Law with Computer Science. Experience in programming, statistical analysis and legal research is a plus. • Knowledge of OR interest in these areas
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research articles, project proposals, and other research-related outputs Support administrative and outreach tasks related to the project Your Profile: Background in geography, geotechnical engineering, or
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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: Professor Dr. Markus Ritter markus.ritter
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calculator (available only in German) Equal opportunities for all: We welcome every additional/new personality to the team! Employment duration: The position is advertised for a period of 4 years, with
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the Institute for Quantum Optics and Quantum Information (IQOQI) of the Austrian Academy of Sciences. We are a member of the Vienna Center for Quantum Science and Technology (VCQ), one of Europe’s largest hubs
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the Institute for Quantum Optics and Quantum Information (IQOQI) of the Austrian Academy of Sciences. We are a member of the Vienna Center for Quantum Science and Technology (VCQ), one of Europe’s largest hubs
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apply: Letter of Motivation (Academic) Curriculum vitae Final Degree certificates (Certificate of completed diploma or master's degree programme) List of publications (if available) evidence of teaching
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laboratory work, as well as teaching in laboratory courses in the Bachelor's programme in Chemistry. The focus here is on instructing students in the evaluation of experimental data and the use of digital