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-induced have been reported at X-ray, optical, and radio wavelengths, but confirmation and characterization has been difficult: the decisive test is whether the emission recurs on the planetary orbital
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(ISCR), is to design electrochemical and optical tools to analyze this process, enabling determination of optimal conditions for surface functionalization. This will require the development of two new
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02.04.2026, Academic staff The research group of Prof. Frank Ortmann at TUM is offering two PhD positions (Research Associates, f/m/d) Start: Summer 2026 (flexible) Research topics: * Optical
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tool for process design and laser-scanning strategies, the integration of simulation and experimental pulse-signal data to characterize lateral energy distribution, and the prediction of material removal
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improve the efficiency of all-perovskite tandem solar cells. The work combines nanophotonic design, optical modelling, materials processing, and device fabrication. The project is embedded in the national
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should be able to carry out research tasks independently yet collaborate effectively with other research investigators. Research Assistant Professor Completion of two or more years of postdoctoral
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of innovative photonic technologies with applications in sensing, diagnostics, and integrated optical systems. Duties and responsibilities The selected candidate will: Design, fabricate, and characterize next
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properties, including excitonic effects and charge carrier dynamics, in high magnetic fields and under optical/THz excitation. Probe light-induced excitations and their coupling to electronic and excitonic
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. Demonstrable experience with data processing, signal analysis and programming (e.g. Python/Matlab). Ability to work independently as well as in a multi-disciplinary team. Fluent in English (oral and written
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Max Planck Institute for Biological Cybernetics, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
interacts with the prefrontal cortex to integrate interoceptive signals and guide higher-order cognition. Combining ultra-high-field layer fMRI at 9.4 Tesla, diffusion MRI, and machine learning in humans with