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  3. 2 PhD positions in atomistic modelling and machine learning for interfaces in energy materials (1.0 FTE)

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2 PhD positions in atomistic modelling and machine learning for interfaces in energy materials (1.0 FTE)

Modelling and computational discovery of energy materials and interpretation of experimental observations with atomistic simulations (DFT) and machine learning.

2 maanden geleden


Domplein, Utrecht, Utrecht
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
38 - 40 uur
€ 2395 - € 3061 per maand


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. Energy 1 (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.


Applicants should have:

  • a master degree in chemistry, physics, materials science, or engineering;
  • background knowledge in first-principles electronic structure theory;
  • experience in scientific programming (experience with GPUs is a plus); and
  • excellent command of both written and spoken English.

Additional experience in one or more of the following areas will be considered an asset:

  • experience with periodic DFT calculations, ideally for surfaces and/or interfaces;
  • materials for electrochemical energy storage/conversion;
  • application of machine learning to materials science;
  • automated (high-throughput) calculations.


  • a full-time position for 4 years;
  • a full-time gross salary starting at €2,395 in the first year and increasing to €3,061 in the fourth year (scale P Collective Labour Agreement Dutch Universities (cao));
  • 8% holiday bonus and 8.3% end-of-year bonus;
  • a pension scheme, partially paid parental leave, and flexible employment conditions based on the Collective Labour Agreement Dutch Universities.

In addition to the employment conditions laid down in the cao for Dutch Universities, Utrecht University has a number of its own arrangements. For example, there are agreements on professional development, leave arrangements and sports. We also give you the opportunity to expand your terms of employment via the Employment Conditions Selection Model. This is how we like to encourage you to continue to grow.

More information about working at the Faculty of Science can be found here.

Additional information

If you have any questions that you’d like us to answer, please contact Dr. Nongnuch Artrith (n.artrith@uu.nl).

Do you have a question about the application procedure or the working conditions at Utrecht University? Please send an email to science.recruitment@uu.nl.