175 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"I.E" positions at ETH Zurich
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core part of your project will be interpreting the data and developing scientific hypotheses about the atmospheric processes that control the cycling of selenium and other trace elements. You will work
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, we collect data through biological monitoring, environmental DNA methods, remote sensing, and field sampling, and use these data to answer questions with statistical and process-based models
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climate-neutral future . Curious? So are we. We look forward to receiving your online application, which should include: A letter of motivation Your CV Contact information for two references
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, data-driven frameworks that enable robust monitoring and condition assessment of infrastructure fleets. By combining smart sensing with distributed intelligence and advanced stochastic modelling
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, and certificates Names and contact details of two referees Further information about the research group can be found on our website . Questions regarding the position should be directed to Prof. Dr
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100%, Zurich, fixed-term We have an open PhD position at the intersection of machine learning, embedded intelligence and human–computer interaction. The project will explore how learning systems can
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tracking of minimally invasive robotic systems Autonomous control in uncertain anatomical environments Computer vision for image-guided robotic procedures (incl. endoscopic, MR-, US-guided) Surgical training
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description ESR15 will primarily focus on the development of metamaterials-based structures and devices that through vibration energy harvesting can exploit structural vibration to power sensors and data
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and BS degrees Contact information of 3 references Applications will be accepted until December 31, 2025. Please note that we exclusively accept applications submitted through our online application
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to complex in vivo environments (Schmidt, Science, 2022), especially in the context of drug-host microbiome interactions, and the development of dedicated tools and analytic workflows for the novel data