46 computer-programmer-"the"-"FEMTO-ST"-"PDI-Service"-"https:" positions at University of Vienna
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of battery materials, at the interface of technical applications, resource management, and sustainability. You independently plan and carry out complex experiments, evaluate the data, and interpret the results
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of research interests / ideas for a prospective doctoral project proposal With a plan for the completion of the doctorate With a confirmation of enrolment in the doctoral programme/having passed the FÖP Via our
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programme of the Vienna Doctoral School of Pharmaceutical, Nutritional and Sport Sciences (VDS PhaNuSpo) and to sign a doctoral thesis agreement within 12-18 months after being employed. The position is
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systems, business administration and/or economics, computer science or a related field. Experience performing and publishing academic research at peer-reviewed conferences and journals is a plus. You are an
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Motivation (Academic) Curriculum vitae Final Degree certificates (Certificate of completed diploma or master's degree programme) List of publications (if available) evidence of teaching experience
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organise scientific events. You prepare and complete a publication-ready habilitation. You hold courses independently in the Bachelor programme „Languages and Cultures of South Asia and Tibet” and the Master
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Data Stewardship program. The Faculty of Earth Sciences, Geography and Astronomy (Fakultät für Geowissenschaften, Geographie und Astronomie / FGGA) is therefore looking for a highly motivated person (m/f
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systems, business administration and/or economics, computer science or a related field. Experience performing and publishing academic research at peer-reviewed conferences and journals is a plus. You are an
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you independently teach courses in the BA program (proseminars), one course per semester in a 50% employment contract you support the professor for Islamic art history in research, teaching and
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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