Dear students and colleaques,
we have an open Post-Doc position for NMR parameter modelling of porous materials in NMR Research Unit.
In the project, we will combine quantum chemical (QC) methods at relativistic level for heavy-element containing systems with atomistic molecular dynamics (MD) simulations utilising modern semi-empirical and machine learning (ML) approaches. The work is carried out in close collaboration with local and international experimental NMR researchers, where modeling is essential part providing predictions and microscopic interpretations of experimental observations. As a post-doctoral researcher, one will focus on developing QM/MD/ML-methods for large length- and time-scale simulations in new porous materials.
For more information, see the application form: https://oulunyliopisto.varbi.com/en/what:job/jobID:660197/
Some related publications:
“ Encapsulation of xenon by bridged resorcinarene cages with high 129Xe NMR chemical shift and efficient exchange dynamics “ https://doi.org/10.1016/j.xcrp.2023.101281
“ Hyper-CEST NMR of metal organic polyhedral cages reveals hidden diastereomers with diverse guest exchange kinetics ” https://www.nature.com/articles/s41467-022-29249-w
“ Inside information on xenon adsorption in porous organic cages by NMR “ https://doi.org/10.1039/C7SC01990D
“ Clathrate Structure Determination by Combining Crystal Structure Prediction with Computational and Experimental 129Xe NMR Spectroscopy “ https://doi.org/10.1002/chem.201604797
“ Encapsulation of Xenon by a Self-Assembled Fe4L6 Metallosupramolecular Cage “ https://pubs.acs.org/doi/10.1021/ja5130176
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