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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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perform advanced synchrotron experiments to probe structural, chemical, and dynamic evolution of defects in thin films and heterostructures. Utilize techniques such as Bragg coherent diffraction imaging
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ecosystem. Key Responsibilities Develop and optimize lithographic patterning of nano- and meso-scale structures, such as gratings, waveguides, cavities, and metamaterials for quantum and THz devices Integrate
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surface-emitting lasers with MHCG subwavelength diffraction grating mirrors): • Optimization by means of computer simulations of MHCG mirrors, • Finding the best strategies for efficient heat flow in
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subwavelength diffraction grating mirrors): Characterization of the devices at every stage of the project (LIV, emission spectra, near-field, far-field, small-signal modulation, etc.) Characterization
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for surface plasmon resonance, grating-coupled interferometry, photometry and multi-angle light scattering, among others. The employer retains the right to change or assign other duties to this position. Focus
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cell handling, differentiation, and organoid formation, while inte-grating automated imaging, quality control, and data analysis. A strong component of the work will be the programming and customization