206 assistant-professor-computer-science-data-"https:"-"https:" uni jobs at ETH Zurich
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2026/01/08) Position Description: Apply 2026/01/08 11:59PM Position Description The Department of Computer Science (www.inf.ethz.ch) at ETH Zurich invites applications for an assistant professorship
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and engineering. Particular emphasis will be placed on contributions to the MSc Statistics and MSc Data Science programs. Assistant professorships have been established to promote the careers of younger
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work closely with Professor Platt, guide the group’s computational research, contribute to ongoing projects, and pursue independent research directions aligned with the laboratory’s goals. Project
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, workshops, and events is also part of your responsibilities, as is serving as an interface between research and administration. Profile Completed university degree (PhD) in mathematics, computer science
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operating and advancing the data platform, assist interdisciplinary projects that integrate multiple data sources, and use high-performance computing resources to manage and process large environmental
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can find more information about the Professorship of Research on Learning and Instruction and the research lab here . You can also contact Professor Dr. Martina Rau (martina.rau@gess.ethz.ch ) with
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institutions worldwide. Further information about Professorship for International Relations and Data Science can be found on our website. Questions regarding the position should be directed to Professor Dr
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of mathematics, computer science, and evolutionary biology. We develop methods to understand evolutionary, ecological, epidemiological, and developmental processes on different scales based on genetic data. In our
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or mechanical engineering, or CS Solid knowledge of computer vision and ML, particularly anomaly detection methods Experience with multimodal data (e.g., image + time series, sensor fusion) is a strong ad-vantage
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, the research group has investigated effects of trainings that help people recognize misleading data visualizations, thereby reducing their negative impact on information extraction (for example, see Rho et al