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Bayesian machine learning to improve risk management for bridge portfolios. We offer a funded PhD position in an excellent research environment. The project Our infrastructure is aging, and decisions about
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10.01.2022, Wissenschaftliches Personal The Chair of Computational Modeling and Simulation (CMS) at Technical University Munich invites applications for the position of a Research Assistant (m/f/d) for performing fundamental research in the frame of the project DrawOn funded by the Bavarian...
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(m/f/d) for performing fundamental research in the framework of the Transregio "Additive Manufacturing in Construction" funded by the German Research Foundation (DFG). The candidate has the opportunity
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, we are currently looking for a committed PhD Student to start on 15/01/2026. The position is part-time (TV-L 13, 65%) and initially limited to 3 years. Research project Advancements in structural
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for analyzing block-like structures made of limestone and granite - Evaluation of data using acoustical imaging techniques and passive seismic monitoring - Carrying out measurements in a team of experts on and in
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team. You will be enrolled in the TUM Graduate School with its structured doctoral program and professional-skills courses. You will contribute to an French-German collaboration on next-generation
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interdisciplinary and international working environment with close collaboration between AI experts and leading clinicians Fully funded PhD position (E13 TV-L) with a structured doctoral pathway Access to unique
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and networking opportunities within the Munich AI ecosystem and within structured graduate programs: the Munich Centre for Machine Learning (MCML), the Munich Data Science Institute (MDSI), the local
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) at Helmholtz Munich and the Chair of Biological Imaging (CBI) at the Technical University of Munich (TUM) are an integrated, multi-disciplinary research structure and form the cornerstone of a rapidly expanding
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, adversarial attacks, and Bayesian neural networks. Excellent analytical, technical, and problem-solving skills Excellent programming skills in Python and PyTorch including fundamental software engineering