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Qualifications Familiar with Ab-initio calculation packages (VASP(plane wave basis set), JAGUAR(Gaussian basis sets), CRYSTAL(hybrid DFT with Gaussian basis sets)), MD simulation software (LAMMPS), bond-detecting
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also exploit machine-learning techniques to train more approximate simulation methods with highly accurate reference DFT results. This will allow simulation of system sizes that are difficult to treat
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) simulations. The use of MLFFs will allow for larger simulation cells and longer timescales to be accessed, whilst retaining the accuracy of DFT calculations, which we hope will allow for more accurate
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experience in DFT and AIMD simulations is required. The candidate is expected to work across RMIT and CSIRO (Clayton). Applicants who meet the eligibility criteria and must enrol by December 2024.
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liquid environment. 1) Molecular Modeling - Study of interactions between MnO₂ and ionic liquids using Density Functional Theory (DFT) and Reactive Molecular Dynamics (ReaxFF). - Analysis of oxidation
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approximate simulation methods with highly accurate reference DFT results. This will allow simulation of system sizes that are difficult to treat with fully ab initio theoretical approaches. Due to the project
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value a willingness to learn and grow in these areas: Prior experience in some sort of computational method such as DFT, tight-binding or Monte Carlo simulations. We are committed to fostering
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for the new green steels compositions, including impurities and tramp elements. These models should enable density-functional-theory (DFT) accurate large scale atomistic simulations of defects including
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density-functional-theory (DFT) accurate large scale atomistic simulations of defects including dislocations, grain boundaries and precipitates, as well as phase diagrams exploration. A key challenge faced
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work duties after employment. Required selection criteria You must have an academically relevant background within AI, or materials-related simulations (DFT, MD, or FEM). You must have a Master's degree