192 data-"https:" "https:" "https:" "https:" "https:" "https:" "UNIV" "UNIV" "UNIV" positions at ETH Zurich
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80%, Zurich, fixed-term The Biomedical Data Science (BMDS) Lab investigates data-driven solutions for healthcare applications with a focus on neurological conditions such as spinal cord injury (SCI
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information for two references, which can be appended to the CV or provided as a separate PDF if you prefer. No reference letters are needed at the time of application, and we will notify you in advance if we
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for this position and group. Research Proposal (1-2 pages) outlining a potential research project you would like to undertake. Contact Information for two academic referees Further information about
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. Further information about NEXUS Personalized Health can be found on our website . Questions regarding the position should be directed to Daniel Stekhoven, stekhoven@nexus.ethz.ch , and David Meyer, meyer
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frames). Project background The work focuses on data-driven generation of structural systems. You will be involved in developing, experimenting with, and evaluating machine learning models that help
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and relevant expertise Names and contact information for three references Academic transcripts (Master’s and PhD), including grade point average and English translations where applicable Please note
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dissolved solids (TDS) are regularly monitored using handheld and automatic probes. Installing and maintaining these instruments, including regular calibration and data acquisition, will be part of your work
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with the following documents: Curriculum vitae Cover letter Names and contact information for three references Academic transcripts (Bachelor’s and Master’s), including grade point average and English
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), highly resolved (hourly‑scale) data on species presence, abundance, and movement patterns in rivers and streams. To address this gap, this project aims to realise the Riverine Organism Drift Imager (RODI
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problems in scientific or engineering domains using proprietary/real data (beyond public benchmarks), where challenges like distributional generalization, multi-objective trade-offs, causality, privacy