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source of inspiration for innovative developments and scientific excellence, it contributes to shaping our society and our future. For over 35 years, the Fraunhofer Institute for Production Systems and
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the application of data science to challenges in (organic) chemistry, with over 15 years of interdisciplinary research. Our data science team develops smart screening strategies and machine learning tools
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for innovation in research and education. Methodological diversity, interdisciplinary collaboration, transdisciplinary cooperation with partners outside academia and a dynamic development characterize its research
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technological disciplines relevant to regenerative medicine and aims to combine excellent training with innovative science and experimental and clinical medicine. The development of novel regenerative therapies
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PhD Position - Organic Electrosynthesis: monitoring of reaction transients with real-time techniques
Your Job: The Electrocatalysis research department (https://www.hi-ern.de/hi-ern/Electrocatalysis) is looking for three PhD students, which research area is to investigate fundamental relationships
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and climate effects. The graduate school guides the doctoral candidates to become highly qualified in their discipline, while at the same time developing competence, interdisciplinary thinking, and
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this project, we aim to establish and operate a fully automated cell culture pipeline for pluripotent stem cells and their derivatives. The position involves developing and maintaining protocols for robust stem
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information, please see: Facts and Figures. ) The University of Tübingen is a member of the European University Alliance “CIVIS – A European Civic University” (https://civis.eu/en ), which offers a wide range
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develop instrumentation to characterise water in situ on the lunar surface. We are currently involved in several flight instrument developments for the European Space Agency, one of which is the Rover
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and odor perception and food-derived proteins. The project aims to make use of the structural information for structure-based ligand design projects in order to develop prediction methods to identify