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for the electrochemical energy storage and conversion. Aiming to develop sustainable and cost-effective batteries, fuel cells, and electrolyzers with improved energy and power density, longer lifetime at maximal safety is
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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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and Electronic and Structural Characterization of Piezoelectric Ternary Metal Nitrides to promote their own academic qualifications within the meaning of Section 2 (1) of the German Academic Fixed-Term
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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Description This PhD project relates with ongoing research projects in the area of renewable energy powered membrane processes, in particular solar-powered electrodialysis at IAMT. The removal
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motivation and curiosity • Ability to work in an interdisciplinary team • Structured and independent way of working • Experience in high-resolution fluorescence microscopy and microfluidics • Practical
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of transmission electron microscopy (TEM/STEM) and/or nanoindentation is an advantage Knowledge of defects, phase transformations, and activation/decay behavior desirable Ability to work in a team within an
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PowerPoint good written and spoken English skills self-motivated, independent and responsible working style and high organisational skills ability to work in a team and willingness to integrate
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, issue tracking). Strong interest in academic research and willingness to pursue a PhD. Independent, structured way of working, quick comprehension, and ability to adapt to new concepts. Excellent
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to planetary, geological and mineral resource research. Email: Audrey.Bouvier(at)uni-bayreuth.de Prof. Dr. Johannes Buchen . Experimental measurements of the physical properties of geomaterials to constrain