251 learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions in Switzerland
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Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students
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diversity and sustainability In line with our values , ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which
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-value experience for participating companies and alignment with institutional objectives. Acquire a thorough understanding of companies and professors' needs and ensure appropriate collaboration models
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virtual environments Strong quantitative skills (R, Python, or Stata; experience with machine learning or advanced experimental methods is a plus) Familiarity with VR-related toolkits (e.g., Unity, Unreal
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, Enviromental, and Geomatic Engineering, has an opening for a PhD student. This position focuses on leveraging vehicle sensors, remote sensing, and machine learning to support modern urban road safety analysis as
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an attractive and supportive workplace, inspire innovative thinking and action, and foster the professional development of your staff. You are proficient in German or willing to acquire German language skills.
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, engineering, and biology, developing new measurement and modelling approaches that transform what is possible to learn from individual cells and from minute amounts of molecular material. Three major research
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March 1, 2027, or by mutual agreement. In line with our values , ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning
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of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website
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, verifier-guided training, and reinforcement learning-based post-training. The goal is to build systems that can justify recommendations, cite supporting evidence, calibrate uncertainty, defer appropriately