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Field
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-ray diffraction, and X-ray photoelectron spectroscopy would also helpful for this position. Basic programming skills (in Python) is another skill desired for this position. We offer DTU is a leading
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simulations. Design, develop, and validate physics-informed AI/ML models with features from electronic structure, spectroscopy to control materials growth and emerging functionalities. Develop and train agentic
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aims to simulate time-evolving supernova-CSM interaction with varying physical parameters, and construct grids of photometry, spectroscopy, and polarimetry based on the radiative output, to be compared
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and designed proteins using a combination of classical and advanced techniques including optical and NMR spectroscopy, surface plasmon resonance, light and X-ray scattering, cryo-electron and
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, and interface structure determination with x-ray diffraction/scattering/spectroscopy, transport and magnetic property characterization using Quantum Design’s MPMS/PPMS and dilution refrigerators
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, and interface structure determination with x-ray diffraction/scattering/spectroscopy, transport and magnetic property characterization using Quantum Design’s MPMS/PPMS and dilution refrigerators
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their nickel complexes, using Schlenk techniques, the glovebox, NMR spectroscopy, mass spectrometry, single-crystal X-ray diffraction and other techniques that might be deemed suitable. You will then test
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for professional development include mentoring undergraduate and graduate researchers, contributing to grant proposals, conducting guest lectures, and learning advanced synchrotron spectroscopy techniques including
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screening. • Data analysis using X-ray crystallography, neutron crystallography, and X-ray spectroscopy approaches. • Applying computational skills to support and collaborate on AI and classical machine
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methodologies. Proven proficiency in thermodynamic modeling using FactSage, CALPHAD, and complementary simulation platforms like Aspen Plus. In-depth knowledge of electron microscopy, spectroscopy, and structural