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-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application
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biology strong theoretical and practical background in organic chemistry (dye chemistry) experience with biological techniques interest in understanding biological processes at the atomic level self-driven
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to extend your specific network, structured supervision of PhD process. Further, the university cares for a family-friendly working environment and offers a family service centre and children’s daycare
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encouraged (e.g. South America, Asia or Africa). The PhD process will be accompanied by in-tegration into TUM’s School of Life Sciences or School of Management and participation in the related Graduate School
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your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guarantee for the protection of your personal data when submitted as
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and ability to express yourself in spoken and written German and English language • Proficient use of common programming languages, MS-office, data storage, and image processing • Ability to support the
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processing • Ability to support the institute’s teaching in tutorials and seminars • Enjoyment of being initiative and liaising with people in the work place • Will to achieve the PhD degree (Promotion) Tasks
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Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing
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the “Financial and corporate research from a long-term perspective” project funded by the Academy of Sciences and Literature in the Academies' Programme. The construction process of the database includes
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Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data