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. The OeAW initiates and maintains partnerships worldwide and represents Austria in international scientific organizations; it cooperates with numerous institutions in the scientific field in order to actively
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Science). Experience in scientific writing and research methods (copy of the Master's thesis, as well as list of publications and presentations, if applicable). High scientific qualification in numerical methods and
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Science). Experience in scientific writing and research methods (copy of the Master's thesis, as well as list of publications and presentations, if applicable). High scientific qualification in numerical methods and
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variety of methods. Generating recombinant bacteria. Testing bacteria for the production of new natural products. Data analysis. Contributing to collaborate projects. Contributing to writing publications
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of the most difficult problems in computational science. The ideal candidate will have prior exposure to modern developments in at least one of these fields: functional analysis, numerical analysis
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What to expect: The minimum gross annual salary on a full-time basis (38,5 h / week) according to the collective agreement is EUR 59.934,--. The actual salary will be determined individually, based on your qualifications and experience. In addition, we offer company benefits, flexible working...
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to invite applications for a University Assistant (Praedoc / PhD Candidate) to join the research team led by Univ. Prof. Olga Mula. Our group’s work sits at the forefront of numerical analysis for Partial
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interest in using computational methods such as cognitive and psychophysiological modeling, (Bayesian) statistics and optimal experimental design, and agent-based modeling to address problems in
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surfaces machine learning methods, and/or the development of novel solutions to the many-body Schrödinger equation. Applicants with proven experience in the development of new computational methods and their
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analysis of classical problems in numerical analysis in the framework of modern algorithms of machine learning. Our ideal candidate will have prior exposure to modern developments in theoretical machine