131 data "https:" "https:" "https:" "https:" positions at Technical University of Munich
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advanced wet-lab experience in molecular biology and in reverse genetic approaches. • You are familiar with FAIR data handling and in silico data analysis. • You work precisely and reliable. YOU FIT TO US
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, functional data analysis, ideally, analysis of NGS/ RNA data • Proficient skills in one or more of the major statistical environments as R and/or Python • Experience working with life scientists would be
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of novel catalysts by electrochemical flow cell measurements that will be coupled to on-line analytics (c.f. https://www.nature.com/articles/s41563-019-0555-5). Specifically, an in-house designed flow cell
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) on the collection and processing of personal data in connection with your application http://go.tum.de/554159. By submitting your application, you confirm that you have taken note of the data protection information
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More Information https://www.mos.ed.tum.de/en/afs/career/our-jobs/planning-uncertainty-copy-1/
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Information https://www.mos.ed.tum.de/en/afs/career/our-jobs/planning-uncertainty-1/
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personal data in the course of the application process pursuant to Art. 13 of the General Data Protection Regulation of the European Union (GDPR) at https://portal.mytum.de/kompass/datenschutz/Bewerbung/. By
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application, you confirm that you have acknowledged the above data protection information of TUM. Kontakt: Philipp Rosner: philipp.rosner@tum.de More Information https://www.mos.ed.tum.de/en/ftm/karriere
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on the nanoscale (previous works e.g.: https://www.nature.com/articles/s41563-019-0555-5). You will also supervise one PhD student who will work on a complementary topic guaranteeing quick output and an ideal
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acknowledged the above data protection information of TUM. Kontakt: Christian Mendl More Information https://www5.in.tum.de/~quanTUMcomputing/