71 computer-programmer-"https:"-"UCL" "https:" "https:" "https:" "https:" "IFM" uni jobs at Technical University of Munich
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Scientist/Steward or Software Developer (f/m/d) to facilitate the development of ProteomicsDB with a good background in bioinformatics, data visualization, big data analytics at best in the context of mass
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submitting your application, you confirm that you have acknowledged the above data protection information of TUM. Kontakt: office.lea@sot.tum.de More Information https://tumapply.aet.cit.tum.de/job/detail
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dedication to experimental work in a chemical laboratory environment and computer programming. • Team player skills and enthusiasm to work in a multi-disciplinary and multi-cultural environment • Excellent
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that you have acknowledged the above data protection information of TUM. Kontakt: Prof. Annette Diefenthaler, applications.mdi@tum.de More Information http://www.mdi.tum.de
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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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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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work at international conferences, and publish in leading journals. Through its Graduate Centre and Talent Factory, TUM supports PhD students and Postdocs by providing a dedicated qualification program
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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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copies of official documents, as we cannot return your materials after the application process is complete. For more detailed information, please visit our Homepage: https://www.epc.ed.tum.de/td
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dynamic team. As part of the newly funded ERC Synergy consortium EPIC, you will develop scalable and robust software to train and apply AI models for regulatory genomics. About us The Chair of Computational