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computational datasets of disordered materials based on density functional theory calculations and training machine learning models to accelerate the predictions. This work will involve collaboration with Assoc
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metal dichaocogenides (TMDs) model the phononic bands of the host material with e.g. density functional theory (DFT) calculate the effect of a strain field on the electronic bands and the phonon modes
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an autonomous framework for setting up, executing, and optimizing complex electronic structure workflows, ranging from ground-state Density Functional Theory (DFT) to many-body perturbation theory methods such as
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(EDA) tools. Experience working with ab-initio methods for materials simulation e.g. Density Functional Theory (DFT). Experience working with large collaborative code projects. Proficiency in applying AI