11 computing-"https:"-"IDAEA-CSIC" "https:" "https:" "https:" Postdoctoral research jobs at Technical University of Munich
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arbeiten und sich mit Problemen befassen, die in molekularen Systemen und heterogenen Materialien auftreten. More details can be found here: https://www.epc.ed.tum.de/ddmm/aktuelles/article/postdoc-position
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are involved in a large number of third-party projects and a large international network. This project is offered as part of a Hans Fischer Senior fellowship through the TUM Institute for Advanced Studies (https
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05.07.2026, Academic staff Our research combines mathematical modeling, numerical simulation, scientific computing, and data-driven methodologies to improve the predictive capabilities and
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applicant has a strong background in computational biophysics, as well as data analysis and solid English-language skills. Previous experience in modeling G protein-coupled receptors or membrane proteins is
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of Numerical Mathematics at the TUM School of Computation, Information and Technology. We strongly encourage applications from women and individuals currently underrepresented in mathematics and computational
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organoid-based research. For more information go to: https://www.bauschlab.org Your Qualification: High motivation, curiosity, and commitment to scientific excellence PhD in stem cell biology, developmental
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. In the ELUD research project, we address the question of if and when learning agents converge to an efficient equilibrium and when this is not the case. ELUD will design new algorithms for computing
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activities. ________________________________________ Candidate Requirements ✅ PhD degree in Engineering, Computer Science, Systems & Control, Statistics, Computational Physics, Computational Chemistry
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related field (e.g. battery technology, automotive engineering, electrical engineering) and have previously completed your master's degree in a technical field, such as mechanical engineering, computer
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are modeled using information theory. We wish to investigate how interleaving can reduce the overhead and computational load due to coding coefficients required in classical linear random network coding