Postdoc in modeling of polaronic and ionic diffusion in battery cathode materials – DTU Energy
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DTU Fotonik
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Kgs. Lyngby, Denmark, Europe

The successful candidate will break new ground in developing methodologies to investigate electronic and ionic transfer mechanisms at battery interfaces. By combining Density Functional Theory (DFT) methods with related techniques, such as constraint-DFT (cDFT), ab initio molecular dynamics (AIMD), and Time-dependent DFT (TD-DFT), the candidate will study charge transfer mechanisms as well as chemical reactions at the solid electrolyte interface (SEI) to predict charge transfer properties and elucidate the SEI formation and ionic transfer through the SEI. Candidates interested in machine learning methods could also pursue the development of equivariant graph neural network for electronic scale simulation of battery materials and large-scale deployment of them in Europe’s largest CPU+GPU supercomputer.

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