75 structures "https:" "https:" "https:" "https:" "NOVA.id" uni jobs at DAAD in Germany
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strengthening education and research in Latin America structural strengthening and regional networking of partner institutions and partner universities Who can apply? University graduates from the following
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numerical groups More information on the Junior Research Group can be found under https://tu-dresden.de/mn/physik/itp/das-institut/ag/arbeitsgruppe-quantum-critical-matter?set_language=en . If you have
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international work environment Scientific excellence and extensive professional networking opportunities A structured PhD program with a comprehensive range of continuing education and networking opportunities
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research with the combined tools of immunology, microbiology, virology, cell biology and molecular biology. For more information, please see https://www.mhh.de/hbrs/zib MD/PhD Molecular Medicine
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of the world's leading research centres. Its research focuses on decoding the structure and function of matter, from the smallest particles of the universe to the building blocks of life. In this way, DESY
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years: https://www.daad.de/en/information-services-for-higher-education-institutions/further-information-on-daad-programmes/gssp/ Doctoral candidates who are admitted but not awarded a scholarship will
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(see https://tu-dresden.de/ing/maschinenwesen/postgraduales/promotion?set_language=en ) knowledge in EcoDesign, climate sciences and life-cycle assessments project management knowledge of the host
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to application at http://www.kseta.kit.edu/application.php . Further information about the KSETA Europe application procedure, available research topics, subjects for doctoral dissertations and the KSETA
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, biochemical interactions and biological functions of small natural product molecules in and from plants and fungi ( https://www.ipb-halle.de/en/ ). Contact details: We are looking forward to receiving your
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, candidates are required to complete a scientific programming task in the subject area of the advertised position: https://www.hpc.uni-wuppertal.de/de/peter-zaspel/challenge-in-bayesian-inference-for-climate