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relevant to this advertised position you are a good English speaker and writer (the lab’s working language) you can describe the knowledge/skills gap you need to fill in order to succeed in your research you
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. Profile Enrollment as a student at ETH Zurich or the University of Zurich in a relevant field, such as computer science, engineering, economics and mathematics Intermediate coding skills in R, Stata
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research and its efforts to put new knowledge and innovations directly into practice. The Laboratory of Metal Physics and Technology (LMPT), part of the Department of Materials at ETH Zurich, conducts
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content imaging for experimental workflows in biology and biochemistry. Project background The SCF's centralized instrument pool is accompanied by expert service provided by staff who offer instrument
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Switzerland's position in AI innovation. Job description As a machine learning research engineer, you will be responsible for developing and maintaining software for training large-scale neural networks, such as
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to solve selected problems. Code and test the proposed solution (PoC), communicate results to stakeholders, and provide final reports of the work done and related outcomes. Present data science results
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for recognizing handwritten mathematics, diagrams, and code, and manage systems that provide timely feedback or rubric-based scoring. In your role focusing on open-source engineering, you'll design clean, modular
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experience in statistical analysis and implementing machine and deep learning models using Keras/TensorFlow and/or PyTorch. You have experience in collaborative coding, version control, and utilizing computer
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. This position is part of a collaborative project funded by the Swiss National Science Foundation, which supports multiple researchers, at ETH Zurich and at partner universities, and focuses on the development
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development of ETH Zurich, aiming to further strengthen its scientific excellence in research and education, reinforcing its position as a globally leading university, and nurturing a positive institutional