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Sciences focuses on developing computer-based approaches, particularly chemoinformatics, molecular modeling and machine learning methods, to predict the biological, medical and toxicological properties
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of Vienna. AICARD aims to transform cardiac research by exploring routine clinical data through advanced machine learning and visualization techniques. As part of our vibrant and interdisciplinary team
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good reasons to want to research and teach at the University of Vienna, there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as personalities
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this sound like you? Then join our accomplished team! About the team: The research group Neuroinformatics develops machine learning methods to study the relation of neural activity and cognitive processes, and
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ability to express yourself both orally and in writing Computer literacy (MS-Office; Imaging Software) Basic experience in academic writing Didactic competences / experience with e-learning Excellent
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by the teams are in particular related to theoretical analysis of classical problems in numerical analysis in the framework of modern algorithms of machine learning. Our ideal candidate will have prior
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profound knowledge of current statistics and omics analysis methods and an understanding of the common fragmentation mechanism of analyzed biomolecules, and current statistics, including machine-learning
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• Computer literacy (MS-Office; Imaging Software) • Basic experience in academic writing • Didactic competences / experience with e-learning • Excellent command of written and spoken English (C1 Level
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) Advanced statistical evaluations (in particular machine learning-based analyses and research syntheses such as scoping/systematic reviews, meta-analyses and meta-science approaches) Leading functions in data
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The University of Vienna is a cosmopolitan hub for more than 10,000 employees, of whom around 7,500 work in research and teaching. They want to do research and teach at a place that suits their