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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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back more than 20 years. Special emphasis of the candidate will be put on the utilization of machine learning, new observation technologies (e.g. MHz laser ranging), and the combined usage of data from
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Biological Insights in Preclinical Glioma ModelsMulti-modal machine learning for predicting Glioma progressionHealthAEye: Deep Learning for Retinal Image Analysis and Disease Monitoring *Life Sciences:Germs
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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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acquisition process, identification of parameters, variational modeling, and generative machine learning methods; see https://imsc.uni-graz.at/mr-dynamo for further details. As part of this research effort, we
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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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society and establish additional connections between existing research areas, such as human-computer interaction, artificial intelligence and machine learning, data science, algorithms, and visualization
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high-throughput synthesis and characterization as well as the use of machine learning approaches. Requirements: · Master degree in Materials Science, Physics, Chemistry or an equivalent degree in