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in Visualization and Data Science, as well as applied research in Human-Computer Interaction and Machine Learning. The research objective of this position is to design and conduct studies on human
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outstanding candidates whose work lies at the intersection of statistics, machine learning, data analytics and modern AI algorithms. This includes, in particular, statistics for high-dimensional and complex
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, both within UM and with external partners. Teach at bachelor’s and master’s level in AI, climate data, machine learning and related topics into your courses. Supervise and mentor PhD candidates, postdocs
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are these impacted by different land use scenarios? How can we use machine learning to predict soil microbiomes from either pristine or agriculturally used soils, predict their functional capacity (e.g. carbon storage
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of computer-aided drug design, pharmacophore modelling, docking and virtual screening. You should be a team player with high social skills You are expected to subscribe to the PhD program of the PhaNuSpo
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courses about parallel computing, computer architecture, programming models and high performance computing. These are your qualifications: Must-haves: • Completed doctoral/PhD studies in Computer Science
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for Associate or Full Professor rank. Candidates must have a PhD in Chemistry, Biochemistry or related area and postdoctoral experience. We are seeking exceptional candidates whose research expertise lies broadly
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-based methods and big data applications and machine learning methods. Research focus will be on feedback processes between erosion, sedimentation, tectonics and climate, and topics could include interplay
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lit. b (postdoc) Limited until: 31.12.2029 Reference no.: 4269 Among the many good reasons to want to research and teach at the University of Vienna, there is one in particular, which has convinced
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AI, we’re assembling a world-class founding team at the cutting edge of earth science and machine learning. We’re hiring a Founding Geoscientist to join us at the ground floor. Next-generation