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Max Planck Institute for Mathematics in the Sciences | Leipzig, Sachsen | Germany | about 2 months ago
. Please apply at https://www.mis.mpg.de/career/postdoc . Email: Postal Mail: Max Planck Institute for Mathematics in the Sciences Inselstr. 22 04103 Leipzig Germany Web Page: www.mis.mpg.de
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Regulation of the European Union (GDPR) at https://portal.mytum.de/kompass/datenschutz/Bewerbung/. By submitting your application, you confirm to have read and understood the data protection information
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. Our program focuses on understanding hostpathogen interactions across species (mice, chickens, pigs, dogs) using well-established viral (e.g., Marek's disease virus, Theiler virus, Hepatitis E
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, with a strong background in solid state physics, quantum magnetism, surface science, and/or nanoscience Experience with scanning probe microscopy and programming in Python Hands-on experience with ultra
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/VKA Secure employment with meaningful work and respectful collaboration Comprehensive onboarding and open knowledge exchange within the team Extensive training and further education programs at our UKE
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Additional benefits such as sports programs, job ticket, company events, cafeteria, and emergency childcare For inquiries, please contact: Prof. Dr. rer. nat. Timo Strünker T 0251 83-58238 Apply now via our
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, probability, and statistical signal processing Familiarity with antenna array signal processing techniques Sound understanding of optimization methods and algorithms Proficiency in Python programming Proven
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(e.g. fuel cells, batteries, heterogeneous catalysts, interfaces) Proficiency in high-level programming languages, e.g. Python Previous supervision of graduate students, as well as laboratory
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The Institute of Virology at the Department of Veterinary Medicine at Freie Universität Berlin is a research and teaching institute headed by Prof. Dr. Benedikt Kaufer. It is part of the Center
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Clinical Cooperation Unit (headed by Prof. Dr. med. Johannes Betge) aims to identify cancer vulnerabilities and uncover mechanisms of treatment resistance by using patient-derived cancer models and high