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. For further information, please contact the Dean of the School of Sustainability, Prof. Dr. Harald Heinrichs (harald.heinrichs@leuphana.de ) or Prof. Dr. Jacob Hörisch (jacob.hoerisch@leuphana.de
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. https://jobs.zalf.de/jobposting/0fb81dd83f07b2a8b4fad2619cdfdef12fc45ef60 The deadline for applications is 10 DECEMBER 2025. If you have any questions regarding the research profile of this position
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(DNA extraction, DNA quality check) Bioinformatic processing and analysis of next-generation sequencing data GIS-based landscape analysis Statistical modelling of the relationship between genetic
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Heiko.Briesen@tum.de http://www.lse.ls.tum.de/en/svt Data Protection Notice : By submitting your application for a position at the Technical University of Munich (TUM), you are transmitting personal data. Please
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Institution: Technical University of Munich (TUM), Germany – 12 months Industrial Partner: GIM Robotics, Finland – 24 months Supervisors: Prof. Achim Lilienthal (TUM), Dr. Jose Peralta (GIM Robotics) Target
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(0) 3834 420 4000 dekanmnf@uni-greifswald.de Please take note of our data protection information that is available at https://www.uni-greifswald.de/en/university/information/jobs/ Where to apply E-mail
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in the context of your application https://portal.mytum.de/kompass/datenschutz/Bewerbung/. By submitting your application, you confirm that you have taken note of TUM's data protection information. TUM
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of the procedure, application documents will be deleted in compliance with data protection regulations. In case of any further queries relating to the field of activity, please contact Dr. Jörg Radtke via email. If
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Additional Information Website for additional job details https://gfz.concludis.de/prj/shw/9e9e1b7ea4e250af8fe1f1865650d42b_0/10880/Wisse… Work Location(s) Number of offers available1Company/InstituteGFZ
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(at)senckenberg.de For more information on the Research Fund, please contact: Prof. Dr. Ottmar Kullmer via e-mail: ottmar.kullmer(at)senckenberg.de . For data protection information on the processing of personal data