15 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at ETH Zurich
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of a dynamic and international group of researchers who share a common vision to contribute to top-level academic research in the fields of machine learning. You will have access to state-of-the-art
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capability to identify and quickly learn the most suitable tools for the research on the go. Interested in topics related to the research, such as computational design, performative design, circular economy in
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100%, Basel, fixed-term In the framework of an SNF-funded project, titled “Restoring high-resolution vision using optogenetics”, explanted human retinae will be investigated and recorded from by
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PhD in Computational Materials Physics or a related area is required. Experience with electronic structure calculations is essential. Familiarity with the use of machine-learning tools in materials
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2025. Profile A PhD (or equivalent doctorate) in Business Administration, Management, or a related field (e.g., Psychology, Sociology, Engineering, or Economics). A strong publication record (or
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of academic output. Presenting the project internally and externally, and preparing material for such presentations. Profile Mandatory Requirements: You have: Demonstrable experience with machine learning tools
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. Profile PhD degree in Mechanical Engineering, Electrical Engineering, Materials Science or related field from a top-notch university Productive candidates with outstanding publication records in stretchable
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modelling and/or empirical analysis. The research will ideally combine insights from economics and e.g. computer science. Profile Applicants should hold a PhD in Economics with a strong economic basis and
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contributing to solutions in the global energy landscape. If you excel in collaborative environments and can bring expertise in some of the areas listed above, we encourage you to apply. Qualifications PhD in
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Applicants should have recently earned a PhD in Economics and should show interest in the topics of the group. The preferred candidate has demonstrated her or his potential to conduct high-quality research