2 PhD positions in atomistic modelling and machine learning for interfaces in energy materials (1.0... (# of pos: 2)

The Materials Chemistry and Catalysis group (MCC) at the Debye Institute for Nanomaterials Science (DINS), Utrecht University, has immediate PhD openings in the area of computational materials science. In these positions, you will apply computational modeling to understand electrochemical energy storage and conversion materials. You will work under the supervision of Assistant Professor Nongnuch Artrith on projects involving the atomistic modeling of surfaces and interfaces with density-functional theory (DFT) and interatomic potentials to understand and predict the properties of electrochemical devices such as batteries and catalysts. You will work in close collaboration with experimental colleagues in the MCC group and at the DINS. A specific focus of the positions will be machine learning-based techniques, including the development of machine-learning potentials with our open-source Atomic Energy Network (ænet) package (http://ann.atomistic.net ).

N. Artrith and A. Urban, Comput. Mater. Sci.114 (2016) 135-150.

N. Artrith, A. Urban, and G. Ceder, Phys. Rev. B 96 (2017) 014112.
N. Artrith, J. Phys. Energy1 (2019) 032002.
A.M. Cooper, J. Kästner, A. Urban, and N. Artrith, npj Comput. Mater.6 (2020) 54.
T. Morawietz and N. Artrith, J. Comput. Aided Mol. Des.35 (2021) 557–586.
A.M. Miksch, T. Morawietz, J. Kästner, A. Urban, and N. Artrith, MLST. 2 (2021) 031001.
N. Artrith, K.. Butler, F.X. Coudert, S. Han, O. Isayev, A. Jain, and A. Walsh, Nat. Chem.13 (2021) 505–508.