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Dral's Group AI-enhanced computational chemistry | LOOKING FOR POSTDOCS WITH DIFFERENT EXPERTISE (QM AND ML METHOD DEVELOPMENT, SOLID-STATE MEHOD DEVELOPMENT, APPLICATIONS AND MORE)

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Tag: New J. Phys.

Machine Learning in Chemistry, Method Development, News

Speeding up quantum dissipative dynamics of open systems with kernel methods

Arif Ullah Mar 25, 2022 Tagged with excited states, ML, MLatom, New J. Phys., publications

In the work published in New Journal of Physics, we combine machine learning (ML) with the …

Speeding up quantum dissipative dynamics of open systems with kernel methods Read more →

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