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engineer novel materials inspired by biological examples. We will build phase-separated biomaterials from the bottom up and quantify them using precision experimental techniques. Cells operate by
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work on the research topic, in collaboration with SDLAA members. Cooperate with partners in Dynaverse on relevant adjacent topics. Prepare and publish results in collaboration meetings, workshops and
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scattering experiments Conduct and disseminate world-class research via publications and conference presentations Represent and actively work on increasing the user base at MLZ Your Profile: A Master and PhD
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Area of research: Scientific / postdoctoral posts Job description: Postdoc positions in Computational Health (f/m/x) 102675 Full time 39 hrs./week Neuherberg near Munich Partial Home Office possible
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Your Job: The joint project PHOENIX - Launch Space Power-to-X plays a central role to align the innovation cycles of P2X technologies with the long-term goals of the energy transition, the European
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Dienst der Länder (TV-L, Public Sector Collective Agreement on Länder) salary scale at level 13. The position can also be filled on a flexible part-time basis with at least 30h/week. About the ISOLUME
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synchrotron beamlines Operando studies for the investigation of relationships between catalyst structure and morphology with its performance (reactivity, selectivity, efficiency) and degradation under realistic
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network with partners from science and industry and take on responsibility at the chair right from the start. In your role as a post-doc, you will combine team and institute-oriented tasks with in-depth
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Postdoc position: mechanisms of autoimmunity & autoinflammation in inborn errors of immunity (m/f/d)
aim of our research is to enhance the molecular understanding of these disorders to enable the use of tailored treatment approaches. We invite highly experienced and motivated candidates for a
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Tübingen offers a combination of high-performance medicine and strong research. The goal of the Carl-Zeiss-Project “Certification and Foundations of Safe Machine Learning Systems in Healthcare” is to enable