185 programming-"https:"-"FEMTO-ST"-"UCL" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at Technical University of Munich
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-MS. (previous works e.g.: https://www.nature.com/articles/s41563-019-0555-5). Ideally, the applicant takes over the co-supervision of selected PhD candidates. We are looking for an individual with a
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. Philipp Benz / Dr. Tian Cheng Hans-Carl-von-Carlowitz-Platz 2, 85354 Freising, GER Phone: +49-8161-71-4590 email: benz@hfm.tum.de & tian.cheng@tum.de Homepage: https://www.lse.ls.tum.de/en/fungbio/home/
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Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM. Kontakt: office.cm@mgt.tum.de More Information https://www.fa.mgt.tum.de
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of personal data in the context of your application https://portal.mytum.de/kompass/datenschutz/Bewerbung/. By submitting your application, you confirm that you have taken note of TUM's data protection
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cell handling, differentiation, and organoid formation, while inte-grating automated imaging, quality control, and data analysis. A strong component of the work will be the programming and customization
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Bachelor and Master programs in (Design studios, seminars, practice-based formats) Lead-role in key dissemination formats, such as international publications, conferences and exhibitions Contribution
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Profile The ideal applicant has a strong background in bioinformatics or computational chemistry, as well as data analysis and solid English-language skills. Experience with programming is highly
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of TUM. Kontakt: andre.stiel@tum.de More Information https://www.helmholtz-munich.de/en/ibmi/rg-ibmi-celleng
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information of TUM. Kontakt: contmech@mw.tum.de More Information https://www.epc.ed.tum.de/ddmm/aktuelles/article/phd-position-in-collaboration-with-bmw-on-data-driven-modeling-of-structural-foams-for-high
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at the Technical University of Munich (TUM) invites applications for one PhD position. The student will work on developing scalable distributed preconditioners in Ginkgo (https://github.com/ginkgo-project/ginkgo