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(ab initio calculations, Molecular dynamics, Computational modeling) and materials science. - Excellent skills and understanding in physical-chemistry of materials. - Excellent verbal and written
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photo-bases. The work will focus on modeling of adiabatic and nonadiabatic photochemical processes to capture excited states dynamics using an array of ab initio molecular dynamics methods for excited
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, molecular dynamics simulations using ab initio and machine-learning potentials, and the development or application of machine-learning tools for feature extraction, property prediction, and inverse molecular
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discovery, design, and synthesis. Expertise in ab initio methods and advanced techniques in quantum many-body theory will also support electronic and magnetic calculation and analysis within the center
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analysis with X-ray and entron diffraction. Property characterisation using a physical property measurement system (PPMS) and a SQUID magnetometer (MPMS). Ab-initio DFT calculations for property predication
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. Develop and apply ab initio computations, molecular dynamics simulations, and machine learning models. Collaborate with other researchers within the group and external partners. Present research findings