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Karlsruher Institut für Technologie (KIT) | Karlsruhe, Baden W rttemberg | Germany | about 2 months ago
Germany Application Deadline 9 Nov 2025 - 22:59 (UTC) Type of Contract To be defined Job Status Other Offer Starting Date 17 Oct 2025 Is the job funded through the EU Research Framework Programme? Not
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Degree Doctoral degree (Dr rer nat) Course location Konstanz Teaching language English Languages All our courses are held in English. Programme duration 6 semesters Beginning Winter and summer
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additional courses offered by other institutions of the University of Freiburg, which may be held in German. Full-time / part-time full-time Programme duration 6 semesters, 8 semesters Beginning Only
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Your Job: You will be part of a research team that applies high-throughput experimentation to accelerate research in the emerging field of electrocatalysis. Production of catalyst inks is one
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Aerospace Centre (DLR), will conduct research on 20 research topics with 25 PhD candidates within the next years. The position comes with access to high performance computing resources and access to training
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platform as a doctoral student? At Fraunhofer IPMS , in collaboration with renowned German and European partners from science and industry, we are developing analog accelerators using novel non-volatile
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Association. Our institute integrates cutting-edge biomolecular research, bioinformatics, and high-performance analytical technologies to explore the complex interactions between the human organism and food
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basic over applied research up to pre-industrial development and is performed in collaboration with national and international partners from university, academy and industry. The institute is part of
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Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD Position – Ad Print4Life DC14 Reference code: 50156137_2
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performance in fuel cell (biogas) and co-electrolysis applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under