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, we need an imaging scheme that captures relevant features at different length scales and integrates them into a single reconstruction volume. This PhD project focuses on learning-based phase retrieval
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that captures relevant features at different length scales and integrates them into a single reconstruction volume. This PhD project focuses on learning-based phase retrieval in the weak holographic regime
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD Position: Deep learning for phase-contrast synchrotron X-ray tomography Reference code: 2026
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thesis is not pre-defined and should be defined by the candidate over the course of the first year. The domain of the PhD thesis must be machine learning and either control theory, path planning, or multi
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of material behavior to the development of the material to the finished component. PhD position on physics-based machine learning modeling for materials and process design Reference code: 980 - 2026/WD 1
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learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement tasks to work with, enhance
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diffraction data where the information extends towards 3-d space. Machine learning offers promising approaches for the solution of complex problems of disorder, ultimately aiming at general and automated
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, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning
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Your Job: The PhD project is methodologically independent and embedded in a multidisciplinary research environment at the interface of artificial intelligence, scientific imaging, and materials
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13.03.2026, Academic staff A fully funded PhD position (initially 75% TV-L E13, increasing to 100% TV-L E13 after 8 months) is available at the Professorship of Optimization and Sustainable Decision