36 data-"https:"-"https:"-"https:"-"https:"-"https:"-"Simons-Foundation" Postdoctoral positions at ETH Zurich
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information for at least two academic referees Further information about the Centre for Radiopharmaceutical Sciences ETH/PSI can be found on our webpage https://radiopharmaceutical-science.ethz.ch/ and
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Übersicht NOMIS Foundation ETH Postdoctoral Fellowship 100%, Zurich, fixed-term Drucken The NOMIS Foundation–ETH Fellowship Programme supports postdoctoral researchers at ETH Zurich within the
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Institute of Technology and Singapore’s National Research Foundation (NRF), as part of the NRF’s CREATE campus. As ETH Zurich's only research centre outside of Switzerland, the centre has
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knowledge of iterative learning control theory with applications to industrial systems Excellent foundation in linear algebra, numerical methods, optimization, and control theory Background in online
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Non-tenure-track/postdoctoral Zürich, Switzerland Apply by Nov 01, 2026 ETH Zurich Institute for Mathematical Research (FIM) Rämistrasse 101 8092 Zürich Switzerland Keyboard shortcuts Map data ©2026
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funded by the Swiss National Science Foundation and is conditional upon admission to the Doctoral Program at ETH Zurich. Workplace Workplace We offer The position is hosted in the Department of
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Labouesse and collaboration with Dr. Philipp Fisch. The position is funded by the Swiss National Science Foundation and is conditional upon admission to the Doctoral Program at ETH Zurich. Workplace
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knowledge, clinical context, and relevant patient-level data to produce reliable, auditable, and uncertainty-aware outputs. A major focus of the position is the development of AI-based reasoning strategies
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platform , published in Nature Communications (https://www.nature.com/articles/s41467-020-18059-7), that enables localized, hyper-efficient delivery of therapeutic compounds to specific brain regions
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are currently offering a fixed-term postdoctoral position in the field of athlete monitoring. Project background Current technologies enable the collection of vast amounts of data from athletes