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Computing. · Experience with High Throughput Calculations will be valued but it is not essential. · Previous knowledge of Density Functional Theory (DFT) and experience with DFT codes will be very highly
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Description Job Duties: Conduct the computational and theoretical research on magnetic and topological properties in van der Waals materials using Density Functional Theory (DFT) calculations, tight-binding and
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build using molecular dynamics, the MACE foundation models and density functional theory. Main Tasks and responsibilities: AI4LSQUANT aims to accelerate quantum modelling by learning fast, accurate
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validate the predictions of the ML models by means of atomistic modeling, in particular density functional theory (DFT) calculations, obtaining simulated electronic and emission spectra for the CDs. Finally
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Physics, Materials Science, Chemistry, Chemical Engineering, Applied Physics, or a closely related field with a focus on computational materials modeling. Density Functional Theory (DFT) for surfaces and
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functional theory (DFT)-based approaches, coupled with effective continuum and/or tight-binding models derived from first-principles calculations. The project is part of a large, multi-institution
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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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advanced characterization methods of inorganic materials and their assemblies, ideally with a focus on battery materials. Demonstrated proficiency in Density Functional Theory (DFT) and/or Molecular Dynamics
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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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, Physics, Computational Chemistry, Nanoscience, Chemical Engineering, or a related field. Strong background in modelling (electro)catalytic processes using periodic density functional theory (DFT) is