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Field
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properties of Li-rich three-dimensional materials for lithium battery cathodes using density functional theory (DFT), molecular dynamics, cluster expansion, machine learning computational techniques. This work
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density functional theory, and atomic-scale simulations to investigate the decomposition of polymers using zeolite catalysts. The successful candidate will employ a combination of density functional theory
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related field are particularly encouraged to apply.We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular
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large-scale MD simulations, ideally with LAMMPS, demonstrated via corresponding roles in publications Experience with density functional theory (DFT) calculations, ideally with VASP, demonstrated via
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using molecular mechanics and hybrid QM/MM methods. Applying density functional theory, correlated wavefunction methods (e.g., MP2, CCSD(T)), and multiconfigurational approaches (e.g., CASSCF, CASPT2
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density functional theory calculations in solids (i.e. use of codes such as Quantum Espresso and/or VASP), to work on correlated electron quantum materials. This will include performing calculations and
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related field are particularly encouraged to apply.We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular
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Cluster Contact: Pr. Johan Jacquemin – johan.jacquemin@um6p.ma Research Activities Develop independent research programs bridging experimental and Density Functional Theory (DFT) simulation of materials
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density matter , High Energy Experimental , High Energy Physics , high energy physics or mathematical physics , High Energy Theory , High Energy Theory Group , High Performance Computing , Holographic
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the development of hierarchical computational materials discovery schemes combining random structure searching, machine learning, atomistic, and density functional theory (DFT) calculations to accurately and