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employment. Starting date: 09.04.2026 Job description:PhD Position: Deep learning for phase-contrast synchrotron X-ray tomography Reference code: 987 - 2026/WP 1 Work location: Hamburg Application deadline
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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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in the weak holographic regime, bridging the gap between micro- and nano-tomography. While propagation-based phase-contrast imaging enhances visualization of soft tissues and weakly attenuating samples
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of Operating Microelectronic Devices by X-ray Diffraction Microscopy Beamline ID01, at the ESRF is a world leading instrument dedicated to micro- and nano-beam X-ray diffraction imaging experiments. It enables
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to the battery and large-scale facility user communities. Develop a characterisation workflow of complementary techniques: combining operando 2DµXRD imaging with in situ µ/nano X-ray Computed Tomography (XCT) and
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This PhD project aims to computationally design improved transparent oxide scintillators for X-ray detection applications. New materials are needed for X-ray detectors because existing detector
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of hadrons and the emergence of gluon saturation in Quantum Chromodynamics (QCD). It focuses on Transverse Momentum Dependent (TMD) parton distributions at small longitudinal momentum fraction (x), a regime
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, planning, performance and analysis of XPCS experiments at PETRA III, European XFEL and other international synchrotron radiation and FEL light sources Contribution on further developing coherent X-ray
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on model surfaces In situ and operando (surface) X-ray scattering studies of catalyst/polymer interfaces Design, optimization, and testing/benchmarking of reactors for in situ and operando studies
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work on the following: Design of an efficient multi-level data acquisition, transport and synchronization digital infrastructure focusing particularly on overall phase coherent operation of the overall