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. The ideal assistant studies in the Bachelor's or the Master's program of the Faculty of Business and Economics. In addition, a high level of self-reliance and an efficient attitude to work is expected
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Curious? So are we. We look forward to receiving your online application with the following documents: Letter of motivation Curriculum vitae Enrolment certificate Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal...
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20%-30%, Zurich, fixed-term The Atmospheric Physics group at the Institute for Atmospheric and Climate Science (IAC), ETH Zurich, has an opening for a Student Research Assistant. We are seeking a
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mentoring programme. Support the development and implementation of training and capacity building of relevant stakeholder groups. Engage with various stakeholders from the private and public sectors as
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Department of Mechanical and Process Engineering/Intelligent Control Systems can be found on website . Questions regarding the position should be directed to Dr. Marianne Schmid Daners, marischm@ethz.ch
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on Facebook. If you have any questions regarding the application process, please feel free to contact us at makerspace@sph.ethz.ch . We would like to point out that the pre-selection is carried out by
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Switzerland Application Deadline 28 Sep 2025 - 21:59 (UTC) Type of Contract Temporary Job Status Part-time Hours Per Week 41 Is the job funded through the EU Research Framework Programme? Not funded by a EU
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position requiring high manual dexterity and technical versatility. You will be expected to switch frequently between diverse tasks such as computational modeling, computer-aided design, manual and CNC
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. Support the regulatory submission process together with internal resources and consultants. Profile Education & Experience: Bachelor’s or Master’s degree in Engineering, Operations, Quality, or a related
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automating the detection of individual tree species in forests using deep learning. Specifically, you will: Focus on the application of deep learning techniques in Python to process spatial and aerial data