20 postdoc-parallel-computing Postdoctoral positions at Technical University of Munich in Postdoctoral
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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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research program focused on developing next‑generation multimodal imaging systems spanning the mesoscopic to microscopic scale. As part of a major research project and supported by extensive national and
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activities. ________________________________________ Candidate Requirements ✅ PhD degree in Engineering, Computer Science, Systems & Control, Statistics, Computational Physics, Computational Chemistry
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have the following: • Ph.D. in electrical engineering, physics, computational science, medical technology, biomedical computing, natural sciences, or a related discipline. • Excellent track record
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22.12.2025, Academic staff We are an interdisciplinary team at the Chair of Safety, Performance and Reliability for Learning Systems, and we are looking for exceptional postdoctoral researchers to join our team. The postdoctoral positions will be full-time (100%, TV-L E13). We are committed to...
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adults actively seek, select, and evaluate information to learn about the world. The lab combines behavioral, computational, and cross-cultural approaches to study curiosity, exploration, and reasoning
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14.12.2022, Academic staff The BMBF-funded position is part of the CoMPS project, which is a multidisciplinary project combining the fields of mathematics, computer science, geophysics, and high
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problems or machine learning more broadly. We are looking for candidates with strong mathematical skills and interests. A requirement for the position is a master’s degree in electrical engineering, computer
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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