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a closely related field within the past 3 years and be under 35 years old. A strong background in condensed matter theory is required. The applicant should be proficient in at least one of the
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Scikit-learn, PyTorch, Openbabel, and RDKit packages. Experience with density functional theory (DFT) calculations. Experience with version control GitHub repositories, and Unix/Linux supercomputing
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with density functional theory (DFT) calculations. Experience with version control GitHub repositories, and Unix/Linux supercomputing environments. Good communication skills, including the ability
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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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, 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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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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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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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
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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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lasers is essential. It will be advantageous with experience on pump-probe spectroscopy and/or supercontinuum generation. Experience with density-functional theory is also of relevance. The applicant must