50 postdoc-computational-fluid-dynamics PhD positions at Technical University of Munich
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Master’s students, supporting their academic and research development. ▪ You will be part of a dynamic international team dedicated to advancing quantum technologies and computing with superconducting qubits
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facilities (sequencing, proteomics and metabolomics). This dynamic setting fosters innovation and teamwork, enabling cutting-edge discoveries in the field of microbiome studies. The candidate will work on a
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16.08.2023, Wissenschaftliches Personal The Chair of Computational Modeling and Simulation (CMS) at the Technical University of Munich invites applications for the position of a Research Assistant
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to the computational complexity of climate models, these will be replaced by physics-informed deep learning surrogates in the aforementioned model coupling. The project will initially focus on one main application
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or computational science Strong mathematical skills and interest in developing new mathematical methods Good knowledge of mathematical/numerical optimization methods or deep learning methods Enthusiasm
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(https://soilsystems.net/ ), a Priority Programme (SPP 2322) funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation). Within SoilSystems, scientists from different disciplines from
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. Candidate´s profile: • Master’s degree in Life Sciences, in Computational Biology or MD degree • Previous research experience in immunology • Experience in flow cytometry, cell culture and in high-dimensional
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through resonant excitation of specific bonds. It will revolutionize the field of biopolymer processing beyond cellulose and yield fundamental insights into supramolecular structure and dynamics in
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to Biodiversity Exploratories, a renowned large scale experiment maintained by a large group of internationally renowned scientists, associated PhD students and Postdocs. • Free access to transferable skill and
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messengers transported by the flow or even the pressure of the fluid itself. In an interdisciplinary team, you will either develop theoretical models of the feedback between flow and network architecture