This position focuses on implementing machine-learning-based closed-loop experimentation at the XUV Free-Electron Laser FLASH to enable robust attosecond-scale measurements and automated optimization of FEL operation. The researcher will analyze electron-spectroscopy diagnostics of ultrashort pulses, develop Python-based data analysis workflows, and correlate machine parameters with photon output to improve experimental control. The role bridges photon science, accelerator physics, and computational methods within the OPTIX project, offering access to advanced laser infrastructure and interdisciplinary collaboration. Responsibilities include experimental work, data interpretation, publication, and conference participation while supporting further academic qualification, including a doctoral degree.