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Field
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materials, new processes and optimised components. Our work is interdisciplinary, international and practical. The scientific questions in our institute range from the production of materials, such as powder
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prevention of human diseases (e.g., Li et al., Nature Metabolism, 2024; Ni et al., Cell Metabolism, 2023; Leung et al., Science Translational Medicine, 2022; Seelbinder et al., Nature Communications, 2023
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to a healthier society in such an inspiring workplace is truly meaningful.“ Get to know us Benefits Career Development: Postdoc program, scientific training & career center with tailored offers
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scientific journals and conferences Your Profile: A doctoral degree in Physics, Materials Science, Computer Science, Data Science, or related fields Proven experience with large language models (LLMs), natural
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for the production of heat pipe components Your Profile: Completed university degree in mechanical engineering, physics, materials science, computational engineering, or a related field, with a PhD or Master degree
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | about 1 month ago
Access to state-of-the-art scientific infrastructure and training (including imaging, scientific computing and data visualization, proteomics, and electronics facilities, and a mechanical workshop
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Berlin, and the Max Planck Institute in Hamburg. Our work combines physics, chemistry, and materials science - pushing the frontiers of quantum materials research. The overarching goal of the Collaborative
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The Leibniz Centre for Tropical Marine Research (ZMT) GmbH (www.leibniz-zmt.de ) is an independent research and teaching institute that provides scientific knowledge for the protection and
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conferences (including presenting your research results) and preparation of scientific publications with Peer-Review Your Profile: Completed university masters degree (physics/chemistry) with a PhD Strong
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, Computer Science or related fields (for PhD); Doctorate in Physics, Computer Science or related fields (for Post-Docs). The positions are funded via the Cluster of Excellence (Machine Learning for Science), the ERC