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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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edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations
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Degree Dr rer nat (Doctor rerum naturalium) PhD (Doctor of Philosophy) Course location Ulm Teaching language English Languages Our international PhD programme is only offered in English. Programme
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fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content The PhD programme offers advanced studies in theoretical and
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international research contexts Your Profile: Excellent Master’s degree in mechanical engineering, energy systems, computational engineering, or a related field Strong background in numerical methods and applied
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and committed team, with excellent technical facilities and strong local, national, and international scientific collaborations. The PhD candidate will participate in the structured program of the Jena
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) position in Materials Engineering with focus on mechanistic study of high corrosion susceptibility of additively manufactured biodegradable Mg and Zn alloys PhD position - Ad Print4Life DC14 - code no. 2025
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on retention processes are still poorly understood. The PhD thesis is part of the joint project TRANSFER, which is jointly funded by the Federal Ministry for Research, Technology and Space (BMFTR) and the
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phases Your profile Excellent Master’s or Diploma degree in medical physics, physics, computer science, medical engineering or a closely related field with a strong interest in data science and