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computational efficiency of large-scale simulations. The Chair of Computational Methods in Civil and Environmental Engineering at the Technical University of Munich (TUM) invites applications for Doctoral
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Postdoctoral Researcher in Semantic Knowledge Engineering & Interoperability in Materials Science in
science, materials engineering, and chemistry focuses on the technical safety of products and processes. As part of the European MaterialsCommons project, BAM is collaborating with international partners
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Position Description The new Collaborative Research Centre "Generalised Motivic Methods in Geometry" (DFG CRC 1785) at the University of Regensburg welcomes applications to PhD and postdoc positions
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At IET-1, we are studying the electrolysis of CO2 for the sustainable conversion of green energy into chemical energy carriers in order to defossilize the chemical industry. The process control and
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Jetzt online bewerben: https://karriere.klinikum.uni-heidelberg.de/index.php?ac=application&jobad_id=28642 PhD/Postdoc – Computational Biology & Multi-Omics (m/f/d) Stellenanzeige merken
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Your profile Experience with working in a cleanroom environment is an advantage, as is experience in fibre optics, handling of pro-cess gases, glass processing, and control engineering A completed
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University of Würzburg - NUCLEATE Excellence Cluster | Oettingen in Bayern, Bayern | Germany | 2 months ago
The Cluster for Nucleic Acid Sciences and Technologies – NUCLEATE invites applications for PhD or Postdoctoral Researchers (f/m/d) at the NUCLEATE Excellence Cluster University of Würzburg, Germany
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of miniaturized imaging technologies. Your Profile: The successful applicant must have the following: • Ph.D. in natural sciences, electrical engineering, physics, optics, medical technology, biomedical computing
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applications for the position of a Research Assistant (PhD Candidate / Postdoctoral Researcher (m/f/d). (Pay grade TV-L E13, 100%; relevant professional experience is recognized in accordance with TV-L
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an advantage Strong background in machine learning for image analysis and computer vision, ideally involving microscopy, time-lapse imaging, or other high-dimensional scientific imaging modalities