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wide range of theoretical perspectives, methodological approaches, and links to educational practice. The interdisciplinary course program focuses on the processes and outcomes of teaching and learning
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/casa-sdl-dbe/pinm ) 3. ProSeC: Bacterial protein secretion: from modeling and data analysis to application (Link: www.fz-juelich.de/de/ibg/daten-ki/casa-sdl-dbe/prosec ) 4. VICAR: In vivo
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link associated with each DC position. * The recruiting organization may decide to interview only those applicants who appear from the information available, to be the most suitable, in terms
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. The project involves close collaboration with experimentalists who provide the relevant data. Machine learning methods will be applied to link experimental (imaging) data to a mechanistic model. The results
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into six subclusters (Hazards, Dietary, Knowledge, Urban, Inequalities, Conflict), three supportive research platforms (Technical Platform, Data Management and Data Science Platform, Outreach and
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CV, cover letter, and contact information for two references, to Prof. Elmar Schiebel at schiebel.elmar@zmbh.uni-heidelberg.de . The PhD student will be a member of the Heidelberg Biosciences
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are listed below. For more information please visit the partner website following the specified link. DC 1 Development of wound healing and antimicrobial nanomaterial to be tested in ex vivo models
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status pursuant to the German Social Code IX (SGB IX) will receive priority for employment. Please submit your detailed application (including CV, cover letter, transcript of records, link to Master thesis
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hybridization, in–vivo electrophysiology data analysis with mice and is tightly linked to independent subprojects involving in-vivo electrophysiology in humans and high-resolution fMRI in awake rats
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. The positions are for a fixed term of three or four years (please check the details in the project link). Further information on the project is available at https://www.fz-juelich.de/de/ibg/daten-ki/casa-sdl-dbe