15 coding-"https:"-"FEMTO-ST"-"Prof"-"AMOLF" "https:" "https:" "https:" "https:" "U.S" uni jobs at ETH Zurich
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environment where philosophy meets data science, public health, medicine, and law? At the Health Ethics & Policy Lab (https://bioethics.ethz.ch ), you will join a team committed to shaping responsible
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community Contribute to R data publication packages washr and fairenough Profile You care about data and code being concise and easily reusable You know how to use standard data science tools (Git, GitHub, R
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(e.g., qualitative coding, statistics, simulation, ML) Publish results in peer-reviewed venues (conferences/journals) and contribute to paper writing Support lab operations as needed (maintaining
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) Unsupervised machine learning and deep learning methods Analysis, visualization, and interpretation of learned design spaces Contributing to research outputs (prototypes, publications, open-source code) Profile
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Infrastructure-as-code tools (e.g. Terraform/openTofu) Automation tools and framework, including CI/CD processes and ecosystem (e.g., Gitlab CI, HashiCorp Vault) Experience with the following is preferred, though
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, ICML, ICLR) Proven ability to conduct independent, high-quality research Proven ability to write well-documented code in Python Strong motivation to work in a collaborative team environment and to
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seamlessly into code Contribute to brand identity: logo development, visual guidelines, style systems Profile Degree in Interaction Design, Visual Communication, Graphic Design, or related field Background as
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related field Solid background in physical optics, experience in interferometry and/or cryogenic optics is an asset Extensive experience with optical design and simulation tools (e.g. Zemax, Code V, FRED
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environments that help learners develop deeper conceptual understanding and problem-solving skills. Topics may include multimodal representations of code, intelligent feedback mechanisms, and the cognitive
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datasets and papers with open data and code that can serve as a basis for these exercises, then adapt these in jupyter notebooks (python or R) for student learning exercises. The Supervisor will advise