97 coding-"https:" "https:" "https:" "https:" "https:" "https:" "Data driven Materials Modeling" uni jobs in Switzerland
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to the President of ETH Zurich, Prof. Dr. Joël Mesot. The closing date for applications is 30 September 2026. Where to apply Website https://www.timeshighereducation.com/unijobs/listing/413369/assistant-professor
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sciences. NCCR Genesis does not aim to provide answers in all fields, but to drive innovative research and achieve decisive progress. Further details on NCCR Genesis are available on its website https://nccr
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Instructions Required Materials Cover letter Current CV Research Statement At least 3 confidential letters of recommendation (requested via Interfolio) Applications must be submitted at: https
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the fundamental principles of nature to innovative technologies for society. The Institute of Theoretical Physics (https://itp.phys.ethz.ch/), D-PHYS, ETH Zurich is seeking to hire a Coordinator who will lead the
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drug delivery platform, published in Nature Communications (https://www.nature.com/articles/s41467-020-18059-7), that enables localized, hyper-efficient delivery of therapeutic compounds to specific
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) at the Singapore-ETH Centre (SEC) (https://fht.ethz.ch)developed and piloted innovative upper limb rehabilitation technologies and evaluated them in a clinical context, both in the hospital and at the home of post
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) Ensuring medical grade software quality following industry best practices for patients' usage at home and for researchers in rehabilitation facilities Designing, coding, and driving the automation of test
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, critical use of AI-assisted tools in research and code development, we treat these as part of the standard toolkit and expect them to be used with judgement Fortran is useful, as parts of our modelling
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. Participating in code reviews to ensure code quality and to provide & receive feedback. Applying IT security best practices, including e.g. Zero Trust and Least Privilege principles. Working with clients
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. Main duties and responsibilities Extract and harden a scoring engine from an existing Python/Streamlit prototype into robust, standalone code Rebuild the data layer from Neo4j to a Python-native graph