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research spectrum covers a unique range. Institute of Material and Process Design The Institute of Material and Process Design is dedicated to the sustainable and ecological development of innovative
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Several PhD positions (f/m/d) in International Research Training Group (iRTG) limits2vision Full PhD
) / Sorbonne Université in Paris (France), two of Europe’s largest institutions in the field of vision research. Together, IOR and IDV host the new l imits2vision research training network to educate the next
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drive the formation of transport carriers within the endosomal network. In this mission, we primarily rely on cryo-ET and subtomogram averaging to visualize molecular machines in reconstituted form
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concentration in the titer Development of a scalable downstream process for the produced siderophores, in particular using two-phase aqueous extraction system Your profile Completed university studies (Master) in
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(master’s or equivalent) with excellent grades in the field of data science, material science, mechanical engineering, physics, or similar, with a strong machine learning or simulation background In-depth
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part of the DFG-funded SFB 1361 “Regulation od DNA Repair and Genome Stability”. The PhD student will profit from collaboration and networking with other research groups, all focusing on understanding
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the structure and function of matter, from the smallest particles of the universe to the building blocks of life. In this way, DESY contributes to solving the major questions and urgent challenges facing science
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Completed university studies (Master/Diploma) in the field of mechanical engineering, physics of related disciplines Enjoy experimental work in international and multidisciplinary teams Communicative
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highly automated, networked mobility, featuring international collaboration with mentors from the USA, Asia, and Europe. TUD and the RTG embody a university culture that is characterized by cosmopolitanism
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(master’s or equivalent) with excellent grades in the field of data science, material science, mechanical engineering, physics, or similar, with a strong machine learning or simulation background In-depth