52 web-programmer-developer-"https:"-"UCL"-"U"-"Bocconi-University" PhD positions at Leibniz
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quantum remote sensing of atoms in the MLT. The new, flexible dye laser systems require hands-on work in optics (spectroscopy, laser physics) and software development for lidar control. Data evaluation is
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The Innovative Electron Microscopy Department develops and applies electron microscopy methodologies for nanoscale and atomic-resolution characterization of soft functional materials and their
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%, limited for 3 years, start: as soon as possible) in the trilateral program “Future Proofing Plants to a Changing Climate” (funded by DFG, UKRI-BBSRC, NSF, USDA-NIFA) Who we are: The research group Symbiosis
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Landscape Research) campus in Müncheberg, near Berlin, and is integrated into regional, national, and international (biodiversity) research networks. Your Tasks Develop and apply methods to extract
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off from the well-known and simple concept of amphiphilicity. We propose an innovative look at intermolecular interaction patterns that we foster and develop in research projects that span a broad range
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. The IOW is committed to actively promoting women in fields where they are underrepresented. For this purpose, the institute has developed a plan to promote equality and has repeatedly been awarded the Total
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The Leibniz Institute for Solid State and Materials Research Dresden e. V. (IFW Dresden) conducts modern materials research on a scientific basis for the development of new and sustainable materials
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funded by the Leibniz Collaborative Excellence program and conducted in cooperation with the Institute of Space Systems at the University of Stuttgart. The position includes setting up a multi-metal lidar
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development. It is one of the world's leading research institutions in its field and offers natural and social scientists from around the world an inspiring environment for excellent interdisciplinary research
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Leibniz Institute of Plant Biochemistry (IPB) in Halle (Saale), Germany, where we are offering a fully-funded PhD position within the DFG Priority Programme SPP2363: “Molecular Machine Learning”. About the