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Field
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quantitative training or research experience Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software package Good communication skills in
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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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Bewerbung, abrufbar unter https://portal.mytum.de/kompass/datenschutz/Bewerbung/. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent
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Freising, Germany Tel. +49 8161 71 3961 patrick.bienert@tum.de https://www.mls.ls.tum.de/en/cropphys/home/ www.tum.de The position is suitable for disabled persons. Disabled applicants will be given
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the application and selection process, please refer to the privacy policy on our homepage at https://www.senckenberg.de/en/imprint/ Please visit our website at www.senckenberg.de for further information about the
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acknowledged the above data protection information of TUM. Kontakt: Christian Mendl More Information https://www5.in.tum.de/~quanTUMcomputing/
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information of TUM. Kontakt: k.alim@tum.de More Information http://www.bpm.ph.tum.de
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to the research and development of dexterous end effectors for a new 6G-based teleoperated surgical robotics system. This position stems out of the large scale 6G-Life project (https://6g-life.de/) and will give
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into existing high-performance frameworks, the fast prototyping of new ideas in individual code, an interest in the entire simulation pipeline: starting from simple algorithms to state-of-the-art applications in