180 coding-"https:" "https:" "https:" "https:" "https:" "https:" "I.E" "Helmholtz Zentrum Geesthacht" positions in Switzerland
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and occurrence, many important phenomena, such as segregation, surface instabilities or jamming, i.e. the transition between a fluid- to solid-like state, are poorly understood. This project explores
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supporting startups and innovators, you will take a hands-on approach yourself, i.e. organizing and running workshops, programs and events, handling communications, overseeing your own budget and expanding
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will be responsible for a range of research tasks, including literature search, data curation, coding for systematic literature reviews, data analysis, and miscellaneous administrative activities (e.g
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code, projects, etc) Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered. For further
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Department of Architecture (DARCH), i.e., digital fabrication, adaptive building components, or building envelopes? Then our 18-month fellowship on integrative research in occupant-centric daylighting and
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of research excellence through peer-reviewed publications Evidence of comittment to reproducibity in bioinformatics through the use of Code Repositories Evidence of ability and experience in handling
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documentation. In all cases, the qualifying degree must have been awarded no more than eight years before the start of the fellowship (i.e. September 1 of the fellowship’s starting year). Official confirmation
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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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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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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