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to supervise PhD, Master and Dr. med (thesis as part of medical studies in Germany) students. The fellow will also have the opportunity to teach as part of the institute’s Masters and doctoral program but will
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master's or diploma degree in computer science or mathematics already successfully completed doctorate confident demeanor and proficient use of German and English (both equivalent to at least B2) expertise
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part of the School of Computation, Information and Technology (CIT) of TUM. The position is for 2 years and follows state regulations in accordance with the Collective Agreement for the Public Service
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sending a photo. Please send your complete application, quoting the reference number080/2025, to the Helmholtz Centre for Infection Research GmbH, Human Resources Department, Inhoffenstr. 7, 38124
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with R, statistical and spatial analysis Excellent communication and teamwork skills Excellent organizational skills Experience with field work in post-disturbance forest conditions (desired) Experience
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to teach as part of the institute’s Masters and doctoral program but will not be required or expected to do so. The salary is paid according to the German TV-L system (the salary agreement for public service
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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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Your Job: QENS and INS experiments to investigate the diffusion dynamics of water and ligand molecules on metal oxide nanoparticle surfaces, accompanied by complementary experimental techniques or theoretical simulations Characterization of the magnetic modes in iron oxide nanoparticles using...
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environment in the fields of science, technology and administration as well as for the education of highly qualified young scientists. The computational imaging group at DESY is concerned with the development
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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