70 assistant-professor-and-data-visualization PhD positions at Technical University of Munich in Germany
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. The group’s work in this area has led to best paper awards at PacificVis and Graph Drawing, with recent publications in IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum
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25.07.2025, Wissenschaftliches Personal Concerning a full position (100 %), we are hiring a Research assistant (f/m/d) at the Chair of Non-destructive Testing in the Project ScanPyramids OUR PROFILE
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, studying health-related (mis-)information on social media and its impact on young adults. The position includes international research collaboration, methodological training, and a supportive work
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resource efficiency. A physics-based model for monitoring the condition of helicopter components is being developed as part of this project. With the help of flight test data, this model is to be calibrated
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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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a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation
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on Responsible Data Science. The PhD positions will be at the intersection of Data Science and Social Sciences and will focus on topics such as Explainable & Fair AI, AI Auditing, AI Alignment, and AI Safety in
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) tailored to the structure and properties of NMR spectral data Supporting the development and application of a self-supervised learning framework for pretraining the foundation model Assisting in the large
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Center (CRC) “Data-driven agile planning for responsible mobility” (AgiMo), funded by the German Research Foundation (DFG). This interdisciplinary center, involving four universities (next to TUM, TU
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privacy-preserved fashion. Research topics include, but not limited to, i) handling distributed DL models with data heterogeneity including non i.i.d, and domain shifts, ii) developing explainability and