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, Openbabel, and RDKit packages. 5. Experience with density functional theory (DFT) calculations. 6. Experience with version control GitHub repositories, and Unix/Linux supercomputing environments. 7
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to) SIESTA (www.siesta-project.org) and its TranSIESTA functionality. SIESTA is a multipurpose first-principles method and program, based on Density Functional Theory, which can be used to describe the atomic
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theory. Experience with field work and basic molecular lab work. Proven track-record in handling high-throughput DNA sequencing data and conducting bioinformatic analyses. A curious, collaborative 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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apply density functional theory and other theoretical methods to understand and support experimental research related to hydrogen production and storage. Central to our approach is close cooperation
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for state-of-the-art high performance computing architectures. Study the dynamics and properties of lattice models of nonequilibrium quantum materials using innovative computational techniques. Collaborate
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infrastructure, we support high-level international research collaborations and diverse teaching opportunities. We also have research groups that develop and apply density functional theory and other theoretical
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, Physics, Computational Chemistry, Nanoscience, Chemical Engineering, or a related field. Strong background in modelling (electro)catalytic processes using periodic density functional theory (DFT) is
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, chemistry, computational science, or a related field. Strong expertise in at least two of the following: density functional theory (DFT)/many-body methods, molecular dynamics (MD), machine learning (ML
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thin films possessing the desired magnitude and direction of the polarization. The successful candidate will perform atomistic simulations, using both density functional theory and classical molecular