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                Particle Acceleration is looking for a PhD Student (f/m/d) Multimodal Reconstruction of Laser-Electron Accelerator Phase Space using Physics-Informed Deep Learning. Your tasks Understand the physical process 
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                , their achievements and productivity to the success of the whole institution. At the Faculty of Physics, Institute of Nuclear and Particle Physics, the Chair of Accelerator Mass Spectrometry and Isotope Research offers 
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                academic qualification which is highly recommended. The research activities of the Chair of Ultrafast Microscopy and Photonics concentrate on many-particle effects and interaction with light in solid matter 
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                and the reaction of surfaces and particles with reducing and oxidizing gas-phase species (e.g. laser-based imaging diagnostics, setup of model reactors, modeling of underlying reactions, multiscale 
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                specialized branch of the immune response primarily orchestrated to combat extracellular particles, by removing or encapsulating them. Main orchestrators are T helper 2 (Th2) and innate Lymphoid cells, which 
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                molecular biology techniques and smFISH. Conduct multi-omics data integration across experimental platforms (e.g. NGS, Imaging time lapse, particle tracing) Collaborate with interdisciplinary research teams 
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                substrates while advancing our understanding of deep learning through dynamical systems theory. You will work with two cutting-edge experimental systems: (1) light-controlled active particle ensembles 
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                and the conditions under which desorption may occur. Little is known about how environmental ageing and transport affect the sorption behavior of plastic particles. In arable soils, key knowledge gaps 
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                phenomena such as the spread of misinformation or the formation of filter bubbles. For this, we rely on rigorous probabilistic methods to model and analyse the intrinsic complexities of these systems 
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                Foundation, and is conducted together with partners from the Universities of Hamburg and Bremen, as well as others. The candidate will use novel particle image velocimetry measurements within the first