267 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"UNIV" positions in Switzerland
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for projects that show unconventional thinking and introduce a unique approach. The focus is on promising ideas of high originality for which preliminary data are not necessarily available (high-risk research
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, using data to inform its decisions, in order to shape the future of education at ETH Zurich. As a student assistant, you will contribute to embedding sustainability and ethics in teaching and learning
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for such purposes in a wide spectrum of industries, with significant breakthroughs in computer vision, natural language processing, and intelligent control. This PhD project aims to develop foundation models (FMs
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multimodal data analysis, with an initial focus on neuroscience. To build this interdisciplinary platform, we invite applications for three PhD-level Research Specialists: Microscopy and Spatial
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multimodal data analysis, with an initial focus on neuroscience. To build this interdisciplinary platform, we invite applications for three PhD-level Research Specialists: Microscopy and Spatial
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publications for this position highlighted Reference letters and/or contact details for three academic and/or professional references (You will be notified before they are contacted) Further information about
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processing (experimental planning, setup, measurements, analysis) Conceptualization and realization of novel setups (hardware integration, optical setups, etc.) Software development (data acquisition and
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, Biostatistics, Software Engineering, Systems Operations, and Screening & Lab Automation. Embedded in this multi-disciplinary environment, the Software Engineering group builds data-centric software products
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will be responsible for a range of research tasks, including literature search, data curation, coding for systematic literature reviews, data analysis, and miscellaneous administrative activities (e.g
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lab / external, we are seeking a post-doctoral researcher to join our team. In the project, we will be analyzing ride-sharing, shared e-scooter and shared bicycle behaviour. We will analyse the data