66 computer-programmer-"https:"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "UCL" uni jobs at Technical University of Munich
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Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM. Kontakt: office.cm@mgt.tum.de More Information https://www.fa.mgt.tum.de
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. Philipp Benz / Dr. Tian Cheng Hans-Carl-von-Carlowitz-Platz 2, 85354 Freising, GER Phone: +49-8161-71-4590 email: benz@hfm.tum.de & tian.cheng@tum.de Homepage: https://www.lse.ls.tum.de/en/fungbio/home/
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information of TUM. Kontakt: contmech@mw.tum.de More Information https://www.epc.ed.tum.de/ddmm/aktuelles/article/phd-position-in-collaboration-with-bmw-on-data-driven-modeling-of-structural-foams-for-high
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copies of official documents, as we cannot return your materials after the application process is complete. For more detailed information, please visit our Homepage: https://www.epc.ed.tum.de/td
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work at international conferences, and publish in leading journals. Through its Graduate Centre and Talent Factory, TUM supports PhD students and Postdocs by providing a dedicated qualification program
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of distributed computing, machine learning, image and text analysis, randomized data structures, high-performance computing, and quantum algorithms. Beyond this research, we aim to support computational thinking
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)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM. Kontakt: anja.boeckl@tum.de More Information https://www.arc.ed.tum.de/en/and
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, dynamics, and interactions in complex environments and live mammalian cells. By combining ultra-high-field NMR with complementary biochemical, computational, and cellular approaches, the project will
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. • Computational efficiency: Designing adaptive and physics-aware strategies (e.g., optimized residual selection, physics-based zooming) for real-time inference. • Practical usability: Developing robust, user
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dynamic team. As part of the newly funded ERC Synergy consortium EPIC, you will develop scalable and robust software to train and apply AI models for regulatory genomics. About us The Chair of Computational